{"id":2872,"date":"2023-02-19T21:56:14","date_gmt":"2023-02-19T21:56:14","guid":{"rendered":"https:\/\/sites.rochester.edu\/sdis\/?page_id=2872"},"modified":"2024-06-07T10:49:02","modified_gmt":"2024-06-07T10:49:02","slug":"publications","status":"publish","type":"page","link":"https:\/\/sites.rochester.edu\/sdis\/mcetin\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"
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Journal Papers<\/h2>\n
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    \n
  1. LG-Sleep: Local and Global Temporal Dependencies for Mice Sleep Scoring<\/a>, Shadi Sartipi, Mie Andersen, Natalie Hauglund, Celia Kj\u00e6rby, Verena Untiet, Maiken Nedergaard, and M\u00fcjdat \u00c7etin, Springer Biomedical Engineering Letters<\/em>, in review.<\/li>\n
  2. CNN-based SAR Image Despeckling with a Logarithmic Discrete Cosine Transform-based Loss<\/a>, Ammar Saleem, Muhammed Burak Alver, and M\u00fcjdat \u00c7etin, IEEE Transactions on Geoscience and Remote Sensing<\/em>, in review.<\/li>\n
  3. Plug-and-Play ADMM Based Radar Range Profile Reconstruction Using Deep Priors<\/a>, Kudret Ak\u00e7ap\u0131nar, N. \u00d6zben \u00d6nhon, \u00d6zg\u00fcr G\u00fcrb\u00fcz, and M\u00fcjdat \u00c7etin, Progress in Electromagnetics Research<\/em>, in review.<\/li>\n
  4. Integrating Learning-based Priors with Physics-based Models in Ultrasound Elasticity Reconstruction<\/a>, Narges Mohammadi, Soumya Goswami, Irteza E. Kabir, Siladitya Khan, Marvin M. Doyley, and M\u00fcjdat \u00c7etin, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control<\/em>, in review.<\/li>\n
  5. On the Detection of Upper Mantle Discontinuities with Radon-Transformed Receiver Functions (CRISP-RF)<\/a>, Tolulope M Olugboji, Ziqi Zhang, Steve Carr, Canberk Ekmek\u00e7i, and M\u00fcjdat \u00c7etin, Geophysical Journal International<\/em>, 2024.<\/li>\n
  6. Subject-Independent Deep Architecture for EEG-based Motor Imagery Classification<\/a>, Shadi Sartipi and M\u00fcjdat \u00c7etin, IEEE Transactions on Neural Systems and Rehabilitation Engineering<\/em>, 2024.<\/li>\n
  7. The Foundations of Computational Imaging<\/a>, James E. Fowler, Charles A. Bouman, M\u00fcjdat \u00c7etin, W. Clem Karl, Brendt Wohlberg, and Jong Chul Ye, IEEE Signal Processing Magazine<\/em>, 2023.<\/li>\n
  8. A Hybrid End-to-End Spatio-Temporal Attention Neural Network with Graph-Smooth Signals for EEG Emotion Recognition<\/a>, Shadi Sartipi, Mastaneh Torkamani-Azar, and M\u00fcjdat \u00c7etin, IEEE Transactions on Cognitive and Developmental Systems<\/em>, 2023.<\/li>\n
  9. \u201cA Computer Vision Approach for Analyzing Label Free Leukocyte Trafficking Dynamics on a Microvascular Mimetic<\/a>,\u201d S. Danial Ahmad, M\u00fcjdat \u00c7etin, Richard E. Waugh, and James L. McGrath, Frontiers in Immunology<\/em>, in review.<\/li>\n
  10. \u201cA Hybrid End-to-End Spatio-Temporal Attention Neural Network with Graph-Smooth Signals for EEG Emotion Recognition<\/a>,\u201d Shadi Sartipi, Mastaneh Torkamani-Azar, and M\u00fcjdat \u00c7etin, IEEE Transactions on Cognitive and Developmental Systems<\/em>, in review.<\/li>\n
  11. \u201cThe Foundations of Computational Imaging<\/a>,\u201d James E. Fowler, Charles A. Bouman, M\u00fcjdat \u00c7etin, W. Clem Karl, Brendt Wohlberg, and Jong Chul Ye, IEEE Signal Processing Magazine<\/em>, accepted.<\/li>\n
  12. \u201cUncertainty Quantification for Deep Unrolling-Based Computational Imaging<\/a>,\u201d Canberk Ekmek\u00e7i and M\u00fcjdat \u00c7etin, IEEE Transactions on Computational Imaging<\/em>, 2022.<\/li>\n
  13. \u201cSpineS: An Interactive Time-Series Analysis Software for Dendritic Spines<\/a>,\u201d A. \u00d6zg\u00fcr Argun\u015fah, Ertun\u00e7 Erdil, Muhammad Usman Ghani, Yazm\u00edn Ramiro Cort\u00e9s, Anna Felicity Hobbiss, Theofanis Karayannis, M\u00fcjdat \u00c7etin, Inbal Israely, and Devrim \u00dcnay, Nature Scientific Reports<\/em>, 2022.<\/li>\n
  14. \u201cCompressive Synthetic Aperture Radar Imaging and Autofocusing by Augmented Lagrangian Methods<\/a>,\u201d Alper G\u00fcng\u00f6r, M\u00fcjdat \u00c7etin, and Emre G\u00fcven, IEEE Transactions on Computational Imaging<\/em>, 2022.<\/li>\n
  15. \u201cVideo-SAR Imaging of Dynamic Scenes Using Low-rank and Sparse Decomposition<\/a>,\u201d Majid Moradikia, Sadegh Samadi, Hamid Reza Hashempour, and M\u00fcjdat \u00c7etin, IEEE Transactions on Computational Imaging<\/em>, 2021.<\/li>\n
  16. \u201cOnline Discriminative Graph Learning from Multi-Class Smooth Signals<\/a>,\u201d Seyed Saman Saboksayr, Gonzalo Mateos, and M\u00fcjdat \u00c7etin, Signal Processing, special issue on Processing and Learning over Graphs in Signal Processing<\/em>, 2021.<\/li>\n
  17. \u201cA Mobile App that Uses Neurofeedback and Multi-sensory Learning Methods Improves Reading Abilities in Dyslexia: A Pilot Study<\/a>,\u201d G\u00fcnet Ero\u011flu, Serap Teber, Kardelen Ert\u00fcrk, Meltem K\u0131rm\u0131z\u0131, Bar\u0131\u015f Ekici, Fehim Arman, Selim Balcisoy, Yusuf Ziya \u00d6zcan, and M\u00fcjdat \u00c7etin, Applied Neuropsychology: Child<\/em>, 2021.<\/li>\n
  18. \u201cPlug-and-Play Synthetic Aperture Radar Image Formation Using Deep Priors<\/a>,\u201d Muhammed Burak Alver, Ammar Saleem, and M\u00fcjdat \u00c7etin, IEEE Transactions on Computational Imaging<\/em>, 2021.<\/li>\n
  19. \u201cPrediction of Reaction Time and Vigilance Variability from Spatio-Spectral Features of Resting-State EEG in a Long Sustained Attention Task<\/a>,\u201d Mastaneh Torkamani-Azar, S\u00fcmeyra Demir Kan\u0131k, Serap Ayd\u0131n, and M\u00fcjdat \u00c7etin, IEEE Journal of Biomedical and Health Informatics<\/em>, 2020.<\/li>\n
  20. \u201cChanges in EEG Complexity with Neurofeedback and Multisensory Learning in People with Dyslexia: A Multiscale Entropy Analysis<\/a>,\u201d G\u00fcnet Ero\u011flu, Mert G\u00fcrkan, Serap Teber, Kardelen Ert\u00fcrk, Meltem K\u0131rm\u0131z\u0131, Bar\u0131\u015f Ekici, Fehim Arman, M\u00fcjdat \u00c7etin, Selim Balc\u0131soy, and Volkan \u00d6zg\u00fcz, Applied Neuropsychology: Child<\/em>, 2020.<\/li>\n
  21. \u201cContext-Aware Confidence Sets for Fine-Grained Product Recognition<\/a>,\u201d \u0130pek Baz, Erdem Y\u00f6r\u00fck, and M\u00fcjdat \u00c7etin, IEEE Access<\/em>, 2019.<\/li>\n
  22. \u201cPseudo-marginal MCMC Sampling for Image Segmentation using Nonparametric Shape Priors<\/a>,\u201d Ertun\u00e7 Erdil, Sinan Y\u0131ld\u0131r\u0131m, Tolga Ta\u015fdizen, and M\u00fcjdat \u00c7etin, IEEE Transactions on Image Processing<\/em>, 2019.<\/li>\n
  23. \u201cImproved DInSAR Time-Series Reconstruction in the Presence of Phase Unwrapping Errors using Huber-norm<\/a>,\u201d Shaharyar Khwaja and M\u00fcjdat \u00c7etin, IET Radar, Sonar & Navigation<\/em>, 2019.<\/li>\n
  24. \u201cEmotionality of Turkish Language and Primary Adaptation of Affective English Norms for Turkish<\/a>,\u201d Mastaneh Torkamani-Azar, S\u00fcmeyra Demir Kan\u0131k, A. Tuba Vardan, \u00c7a\u011fla Ayd\u0131n, and M\u00fcjdat \u00c7etin, Current Psychology<\/em>, 2019.<\/li>\n
  25. \u201cJoint SAR Imaging and Multi-Feature Decomposition from 2-D Undersampled Data Via Low-Rankness plus Sparsity Priors<\/a>,\u201d Majid Moradikia, Sadegh Samadi, and M\u00fcjdat \u00c7etin, IEEE Transactions on Computational Imaging<\/em>, 2019.<\/li>\n
  26. \u201cTracking-assisted Detection of Dendritic Spines in Time-Lapse Microscopic Images<\/a>,\u201d Lavdie Rada, Bike K\u0131l\u0131\u00e7, Ertun\u00e7 Erdil, Yazm\u00edn Ramiro-Cort\u00e9s, Inbal Israely, Devrim \u00dcnay, M\u00fcjdat \u00c7etin, and A. \u00d6zg\u00fcr Argun\u015fah, Neuroscience<\/em>, 2018.<\/li>\n
  27. \u201cFast Target Detection in Radar Images using Rayleigh Mixtures and Summed Area Tables<\/a>,\u201d Fatih Nar, O. Erman Okman, Atilla \u00d6zg\u00fcr, and M\u00fcjdat \u00c7etin, Digital Signal Processing, special issue on Reproducible Research in Signal Processing<\/em>, to appear. (Invited Paper)<\/li>\n
  28. \u201cRmSAT-CFAR: Fast and Accurate Target Detection in Radar Images<\/a>,\u201d Fatih Nar, O. Erman Okman, Atilla \u00d6zg\u00fcr, and M\u00fcjdat \u00c7etin, SoftwareX, special issue on Reproducible Research in Signal Processing<\/em>, to appear. (Invited Paper)<\/li>\n
  29. “Image Segmentation Using Disjunctive Normal Shape and Appearance Priors<\/a>,\u201d Fitsum Mesadi, Ertunc Erdil, M\u00fcjdat \u00c7etin and Tolga Ta\u015fdizen, IEEE Transactions on Medical Imaging<\/em>, accepted.<\/li>\n
  30. “Nonparametric Joint Shape and Feature Priors for Image Segmentation<\/a>,\u201d Ertunc Erdil, M. Usman Ghani, Lavdie Rada, A. \u00d6zg\u00fcr Argun\u015fah, Devrim \u00dcnay, Tolga Ta\u015fdizen and M\u00fcjdat \u00c7etin, IEEE Transactions on Image Processing<\/em>, vol. 26, no. 11, pp. 5312-5322, November 2017.<\/li>\n
  31. “Disjunctive Normal Parametric Level Set With Application to Image Segmentation<\/a>,” Fitsum Mesadi, M\u00fcjdat \u00c7etin, and Tolga Ta\u015fdizen, IEEE Transactions on Image Processing<\/em>, vol. 26, no. 6, pp. 2618-2631, June 2017.<\/li>\n
  32. “Recursive Bayesian Coding for BCIs<\/a>,” Matt Higger, Fernando Quivira, Murat Akcakaya, Mohammad Moghadamfalahi, Hooman Nezamfar, M\u00fcjdat \u00c7etin, and Deniz Erdogmus IEEE Transactions on Neural Systems and Rehabilitation Engineering,<\/em> vol. 25, no. 6, pp. 704-714, June 2017.<\/li>\n
  33. “Sparse Representation-based Algorithm for Joint SAR Image Formation and Autofocus<\/a>,” Mohammad Javad Hasankhaan, Sadegh Samadi, and M\u00fcjdat \u00c7etin, Signal, Image and Video Processing,<\/em> vol. 11, no. 4, pp. 589\u2013596, May 2017.<\/li>\n
  34. “Electroencephalographic Identi\fers of Motor Adaptation Learning<\/a>,” Ozan \u00d6zdenizci, Mustafa Yal\u00e7\u0131n, Ahmetcan Erdo\u011fan, Volkan Pato\u011flu, Moritz Grosse-Wentrup, and M\u00fcjdat \u00c7etin, Journal of Neural Engineering<\/em>, vol. 14, no. 4, pp. 13, April 2017.<\/li>\n
  35. “Compressed Sensing ISAR Reconstruction considering High Maneuvering Motion<\/a>,” Shaharyar Khwaja and M\u00fcjdat \u00c7etin, Electronics, special issue on Radio and Radar Signal Processing<\/em>, vol. 6, no. 1, pp. 21-49, March 2017 (Invited Paper).<\/li>\n
  36. “Dendritic Spine Classification using Shape and Appearance Features based on Two-Photon Microscopy<\/a>,” M. Usman Ghani, Fitsum Mesadi, S\u00fcmeyra Demir Kan\u0131k, A. \u00d6zg\u00fcr Argun\u015fah, Anna Felicity Hobbiss, Inbal Israely, Devrim \u00dcnay, Tolga Ta\u015fdizen, and M\u00fcjdat \u00c7etin, Journal of Neuroscience Methods<\/em>, vol. “279”, pp. 13\u201321, March 2017.<\/li>\n
  37. “SAR Moving Object Imaging Using Sparsity Imposing Priors<\/a>,” \u00d6zben \u00d6nhon and M\u00fcjdat \u00c7etin, EURASIP Journal on Advances in Signal Processing, special issue on Advanced Techniques for Radar Signal Processing<\/em>, vol. 2017, no. 1, pp. 10, January 2017<\/li>\n
  38. “An Augmented Lagrangian Method for Complex-Valued Compressed SAR Imaging<\/a>,” H. Emre G\u00fcven, Alper G\u00fcng\u00f6r, and M\u00fcjdat \u00c7etin, IEEE Transactions on Computational Imaging,<\/em> vol. 2, no. 3, pp. 235-250, September 2016.<\/li>\n
  39. “Covariance Matrix Estimation for Interest-Rate Risk Modeling via Smooth and Monotone Regularization<\/a>,” Dmitry M. Malioutov, Aycan A. Corum, and M\u00fcjdat \u00c7etin, IEEE Journal of Selected Topics in Signal Processing,<\/em> vol. 10, no. 6, pp. 1006-1014, September 2016.<\/li>\n
  40. “Asynchronous Decoding of Finger Movements from ECoG Signals using Long-Range Dependencies through Conditional Random Fields<\/a>,” Jaime Fernando Delgado Saa, Adriana de Pesters, and M\u00fcjdat \u00c7etin, Journal of Neural Engineering,<\/em> vol. 13, no. 3, p. 036017, June 2016.<\/li>\n
  41. “Sparsity-Driven Bandwidth-Efficient Decentralized Tracking in Visual Sensor Networks<\/a>,”
    \nSerhan Cosar and M\u00fcjdat \u00c7etin, Computer Vision and Image Understanding,<\/em> vol. 139, pp. 40-58, October 2015.<\/li>\n
  42. “On the Quality and Timeliness of Fusion in a Random Access Sensor Network<\/a>,” Abdurrahim Soganli, Ozgur Ercetin, and M\u00fcjdat \u00c7etin, IEEE Signal Processing Letters,<\/em> vol. 22, no. 9, pp. 1259-1263, September 2015.<\/li>\n
  43. “Word-level Language Modeling for P300 Spellers based on Discriminative Graphical Models<\/a>,” Jaime Fernando Delgado Saa, Adriana de Pesters, Dennis McFarland, and M\u00fcjdat \u00c7etin, Journal of Neural Engineering,<\/em> vol. 12, no. 2, p. 026007, April 2015.<\/li>\n
  44. “Optimization of Decentralized Random Field Estimation Networks under Communication Constraints through Monte Carlo Methods<\/a>,” Murat Uney and M\u00fcjdat \u00c7etin, Digital Signal Processing,<\/em> vol. 34, pp. 16-28, November 2014.<\/li>\n
  45. “Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, Autofocusing, Moving Targets, and Compressed Sensing <\/a>,” M\u00fcjdat \u00c7etin, Ivana Stojanovic, N. Ozben Onhon, Kush R. Varshney, Sadegh Samadi, W. Clem Karl, and Alan S. Willsky, IEEE Signal Processing Magazine,<\/em> vol. 31, no. 4, pp. 27-40, July 2014.<\/li>\n
  46. “Feature Compression: A Framework for Multi-View Multi-Person Tracking in Visual Sensor Networks<\/a>,” Serhan Cosar and M\u00fcjdat \u00c7etin, Journal of Visual Communication and Image Representation,<\/em> vol. 25, no. 5, pp. 864-873, July 2014.<\/li>\n
  47. “Combining Learning-based Intensity Distributions with Nonparametric Shape Priors for Image Segmentation<\/a>,” Abdurrahim Soganli, Gokhan Uzunbas, and M\u00fcjdat \u00c7etin, Springer Signal, Image and Video Processing,<\/em> vol. 8, no. 4, pp. 789-798, May 2014.<\/li>\n
  48. “Compressed Sensing of Monostatic and Multistatic SAR<\/a>,” Ivana Stojanovic, M\u00fcjdat \u00c7etin, and W. Clem Karl, IEEE Geoscience and Remote Sensing Letters,<\/em> vol. 10, no. 6, pp. 1444-1448, November 2013.<\/li>\n
  49. “Discriminative Methods for Classification of Asynchronous Imaginary Motor Tasks From EEG Data<\/a>,” Jaime Fernando Delgado Saa and M\u00fcjdat \u00c7etin, IEEE Transactions on Neural Systems and Rehabilitation Engineering,<\/em> vol. 21, no. 5, pp. 716-724, September 2013.<\/li>\n
  50. “Multiple Feature-Enhanced SAR Imaging using Sparsity in Combined Dictionaries<\/a>,” Sadegh Samadi, M\u00fcjdat \u00c7etin, and Mohammad Ali Masnadi-Shirazi, IEEE Geoscience and Remote Sensing Letters,<\/em> vol. 10, no. 4, pp. 821-825, July 2013.<\/li>\n
  51. “A Latent Discriminative Model-Based Approach for Classification of Imaginary Motor Tasks from EEG Data<\/a>,” Jaime Fernando Delgado Saa and M\u00fcjdat \u00c7etin, Journal of Neural Engineering,<\/em> 9, 026020, 2012.<\/li>\n
  52. “A Sparsity-driven Approach for Joint SAR Imaging and Phase Error Correction<\/a>,” Ozben Onhon and M\u00fcjdat \u00c7etin, IEEE Trans. Image Processing,<\/em> vol. 21, no. 4, pp. 2075-2088, April 2012.<\/li>\n
  53. “Sparsity-driven Ultrasound Imaging<\/a>,” Ahmet Tuysuzoglu, Jonathan M. Kracht, M\u00fcjdat \u00c7etin, Robin Cleveland, and W. Clem Karl, Journal of the Acoustical Society of America,<\/em> vol. 131, no.2, pp. 1271-1281, February 2012.<\/li>\n
  54. “Monte Carlo Optimization of Decentralized Estimation Networks Over Directed Acyclic Graphs Under Communication Constraints<\/a>,” Murat Uney and M\u00fcjdat \u00c7etin, IEEE Trans. Signal Processing,<\/em> vol. 59, no. 11, pp. 5558-5576, November 2011.<\/li>\n
  55. “Parameter Selection in Sparsity-driven SAR Imaging<\/a>,” Ozge Batu and M\u00fcjdat \u00c7etin, IEEE Trans. Aerospace and Electronic Systems,<\/em> vol. 47, no. 4, pp. 3040-3050, October 2011.<\/li>\n
  56. “A Graphical Model based Solution to the Facial Feature Point Tracking Problem<\/a>,” Serhan Cosar and M\u00fcjdat \u00c7etin, Image and Vision Computing,<\/em> vol. 29, no. 5, pp. 335-350, April 2011.<\/li>\n
  57. “Sparse Representation-Based Synthetic Aperture Radar Imaging<\/a>,” Sadegh Samadi, M\u00fcjdat \u00c7etin, and Mohammad Ali Masnadi-Shirazi, IET Radar, Sonar & Navigation,<\/em> vol. 5, no. 2, pp. 182-193, February 2011.<\/li>\n
  58. “Coupled Non-Parametric Shape and Moment-Based Inter-Shape Pose Priors for Multiple Basal Ganglia Structure Segmentation<\/a>,” Gokhan Uzunbas, Octavian Soldea, Devrim Unay, M\u00fcjdat \u00c7etin, Gozde Unal, Ayt\u00fcl Er\u00e7il, and Ahmet Ekin, IEEE Trans. Medical Imaging,<\/em> vol. 29, no. 12, pp. 1959-1978, December 2010.<\/li>\n
  59. “Sparsity and Compressed Sensing in Radar Imaging<\/a>,” Lee Potter, Emre Ertin, Jason T. Parker, and M\u00fcjdat \u00c7etin, Proceedings of the IEEE,<\/em> vol. 98, no. 6, pp. 1006-1020, June 2010.<\/li>\n
  60. “Learning the Dynamics and Time-Recursive Boundary Detection of Deformable Objects<\/a>,” Walter Sun, M\u00fcjdat \u00c7etin, Raymond Chan, and Alan S. Willsky, IEEE Trans. Image Processing,<\/em> vol. 17, no. 11, pp. 2186-2200, November 2008.<\/li>\n
  61. “Sparse Signal Representation in Structured Dictionaries with Application to Synthetic Aperture Radar<\/a>,” Kush R. Varshney, M\u00fcjdat \u00c7etin, John W. Fisher III, and Alan S. Willsky, IEEE Trans. Signal Processing,<\/em> vol. 56, no. 8, pp. 3548-3561, August 2008.<\/li>\n
  62. “Nonparametric Shape Priors for Active Contour-based Image Segmentation<\/a>,” Junmo Kim, M\u00fcjdat \u00c7etin, and Alan S. Willsky, Signal Processing,<\/em> vol. 87, no. 12, pp. 3021-3044, December 2007.<\/li>\n
  63. “Distributed Fusion in Sensor Networks: A Graphical Models Perspective<\/a>,” M\u00fcjdat \u00c7etin, Lei Chen, John W. Fisher III, Alexander T. Ihler, Randolph L. Moses, Martin J. Wainwright, and Alan S. Willsky, IEEE Signal Processing Magazine,<\/em> vol. 23, no. 4, pp. 42-55, July 2006.<\/li>\n
  64. “Data Association based on Optimization in Graphical Models with Application to Sensor Networks<\/a>,” Lei Chen, Martin Wainwright, M\u00fcjdat \u00c7etin, and Alan S. Willsky, Mathematical and Computer Modelling, Special Issue on Optimization and Control for Military Applications,<\/em> vol. 43, nos. 9-10, pp. 1114-1135, May 2006.<\/li>\n
  65. “Variational Approaches on Discontinuity Localization and Field Estimation in Sea Surface Temperature and Soil Moisture Interpolations<\/a>,” Walter Sun, M\u00fcjdat \u00c7etin, W. Carlisle Thacker, T. Mike Chin, and Alan S. Willsky, IEEE Trans. Geoscience and Remote Sensing,<\/em> vol. 44, no. 2, pp. 336-350, February 2006.<\/li>\n
  66. “A Feature-Preserving Regularization Method for Complex-valued Inverse Problems with Application to Coherent Imaging<\/a>,” M\u00fcjdat \u00c7etin, W. Clem Karl, and Alan S. Willsky, Optical Engineering,<\/em> vol. 54, no. 1, 017003, January 2006.<\/li>\n
  67. “A Nonparametric Statistical Method for Image Segmentation using Information Theory and Curve Evolution<\/a>,” Junmo Kim, John W. Fisher III, Anthony Yezzi, Jr., M\u00fcjdat \u00c7etin, and Alan S. Willsky, IEEE Trans. Image Processing,<\/em> vol. 14, no. 10, pp. 1486-1502, October 2005.<\/li>\n
  68. “A Sparse Signal Reconstruction Perspective for Source Localization with Sensor Arrays<\/a>,” Dmitry M. Malioutov, M\u00fcjdat \u00c7etin, and Alan S. Willsky, IEEE Trans. Signal Processing, <\/em> vol. 53, no. 8, pp. 3010-3022, August 2005.<\/li>\n
  69. “Region-Enhanced Passive Radar Imaging<\/a>,” M\u00fcjdat \u00c7etin and Aaron Lanterman, IEEE Proceedings Radar, Sonar & Navigation, Special Issue on Passive Radar Systems,<\/em> vol. 152, no. 3, pp. 185-194, June 2005.<\/li>\n
  70. “Feature Enhancement and ATR Performance using Non-Quadratic Optimization-based SAR Imaging<\/a>,” M\u00fcjdat \u00c7etin, W. Clem Karl, and David A. Casta\u00f1on, IEEE Trans. Aerospace and Electronic Systems,<\/em> vol. 39, no. 4, pp. 1375-1395, October 2003.<\/li>\n
  71. “Feature-enhanced synthetic aperture radar image formation based on nonquadratic regularization<\/a>,” M\u00fcjdat \u00c7etin and W. Clem Karl, IEEE Trans. Image Processing,<\/em> vol. 10, no. 4, pp. 623-631, April 2001.<\/li>\n
  72. “ Balancing and attitude control of double and triple inverted pendulums<\/a>,” G. A. Medrano-Cerda, E. E. Eldukhri, and M. \u00c7etin, Transactions of the Institute of Measurement and Control, <\/em>vol. 17, no. 3, pp. 143-154, 1995.<\/li>\n<\/ol>\n
    \n

    Book Chapters<\/h2>\n
    \n<\/div>\n
      \n
    1. “Optimization and Learning-based Methods for Radar Imaging with Sparse and Limited Apertures Sparse Arrays in SAR,” Ammar Saleem, Alper G\u00fcng\u00f6r, Burak Alver, Emre G\u00fcven, and M\u00fcjdat \u00c7etin, in Sparse Arrays for Radar, Sonar, and Communications,<\/em> M. Amin (ed.), Wiley & IEEE Press, to appear.<\/li>\n
    2. “Compressed Sensing Methods for Radar Imaging in the Presence of Phase Errors and Moving Objects,” Ahmed Shaharyar Khwaja, \u00d6zben \u00d6nhon, and M\u00fcjdat \u00c7etin, in Compressed Sensing-based Radar Signal Processing,<\/em> A. De Maio, Y. Eldar, and A. Haimovich (eds.), Cambridge University Press, 2019.<\/li>\n
    3. “Decentralized Human Tracking in Visual Sensor Networks: Using Sparse Representation for Efficient Communication,” Serhan Cosar and M\u00fcjdat \u00c7etin, in Human Behaviour Understanding in Networked Sensing,<\/em> P. Spagnolo, P. L. Mazzeo and C. Distante (eds.), Springer, pp. 45-73, 2014 (ISBN: 978-3-319-10806-3).<\/li>\n
    4. “Sparsity and Compressed Sensing in Mono-static and Multi-static Radar Imaging,” Ivana Stojanovic, M\u00fcjdat \u00c7etin, and W. Clem Karl, in Compressed Sensing and Sparse Filtering,<\/em> A. Carmi, L. Mihaylova, and S. J. Godsill (eds.), Springer, pp. 395-421, 2014 (ISBN: 978-3642383984).<\/li>\n
    5. “Machine Learning Systems for Detecting Driver Drowsiness,” Esra Vural, M\u00fcjdat \u00c7etin, Ayt\u00fcl Er\u00e7il, Gwen Littlewort, Marian Bartlett, and Javier Movellan, in In-Vehicle Corpus and Signal Processing for Driver Behavior,<\/em> K. Takeda, J.H.L. Hansen, H. Erdogan, and H. Abut (eds.), Springer, pp. 97-110, November 2008 (ISBN: 978-0387795812).<\/li>\n
    6. “Datamining spontaneous facial behavior with automatic expression coding,” Marian Bartlett, Gwen Littlewort, Javier Movellan, Esra Vural, Kang Lee, M\u00fcjdat \u00c7etin, and Ayt\u00fcl Er\u00e7il, in Verbal and Nonverbal Features of Human-Human and Human-Machine Interaction,<\/em> A. Esposito, N.G. Bourbakis, N. Avouris, and I. Hatzilygeroudis (eds.), Springer, Lecture Notes in Computer Science 5042, pp. 1-21, October 2008 (ISBN: 978-3540708711).<\/li>\n
    7. “Graphical Models and Fusion in Sensor Networks,” M\u00fcjdat \u00c7etin, Lei Chen, John W. Fisher III, Alexander T. Ihler, O. Patrick Kreidl, Randolph L. Moses, Martin J. Wainwright, Jason L. Williams, and Alan S. Willsky, in Wireless Sensor Networks: Signal Processing and Communications Perspectives,<\/em> A. Swami, Q. Zhao, Y.-W. Hong, and L. Tong (eds.), John Wiley and Sons, pp. 215-249, December 2007 (ISBN: 978-0470035573).<\/li>\n<\/ol>\n
      \n

      Conference Papers<\/h2>\n
      \n<\/div>\n
        \n
      1. IOL Position Estimation from the Full Shape Geometry of the Crystalline Lens and Machine Learning Algorithms<\/a>, S. Eduardo Martinez-Enriquez, Derick Ansah, Gonzalo Velarde-Rodr\u00edguez, Yue Zhao, U\u011fur \u00c7elik, Scott MacRae, M\u00fcjdat \u00c7etin, Jen-Li Dong, Yuli Lim, Li Wang, Douglas Donald Koch, Nicol\u00e1s Alejandre-Alba, and Susana Marcos, Congress of the European Society of Cataract and Refractive Surgeons (ESCRS)<\/em>, in review.<\/li>\n
      2. Robust EEG-based Emotion Recognition using an Inception and Two-sided Perturbation Model<\/a>, Shadi Sartipi and M\u00fcjdat \u00c7etin, International Conference of the IEEE Engineering in Medicine and Biology Society<\/em>, in review.<\/li>\n
      3. Estimation of the IOL Position using the Full Shape of the Crystalline Lens and Machine Learning Algorithms<\/a>, S. Eduardo Martinez-Enriquez, Yue Zhao, Derick Ansah, U\u011fur \u00c7elik, Scott MacRae, M\u00fcjdat \u00c7etin, Jen-Li Dong, Yuli Lim, Li Wang, Douglas D. Koch, and Susana Marcos, Association for Research in Vision and Ophthalmology (ARVO) Annual Meeting<\/em>, 2024.<\/li>\n
      4. Prediction of Postoperative IOL Tilt from Preoperative 3D OCT Imaging and Machine Learning<\/a>, Derick Ansah, Eduardo Martinez-Enriquez, Yue Zhao, U\u011fur \u00c7elik, M\u00fcjdat \u00c7etin, Jen-Li Dong, Yuli Lim, Li Wang, Douglas D. Koch, Scott MacRae, and Susana Marcos, Association for Research in Vision and Ophthalmology (ARVO) Annual Meeting<\/em>, 2024.<\/li>\n
      5. Multi-Source Domain Adaptation with Transformer-based Feature Generation for Subject-Independent EEG-based Emotion Recognition<\/a>, Shadi Sartipi and M\u00fcjdat \u00c7etin, IEEE International Conference on Acoustics, Speech and Signal Processing<\/em>, 2024.<\/li>\n
      6. Seeing into the Mantle by Sifting through Echoes, Reverbs & Noise<\/a>, Tolulope M Olugboji, Ziqi Zhang, Canberk Ekmek\u00e7i, M\u00fcjdat \u00c7etin, and Steve Carr, American Geophysical Union (AGU) Annual Meeting<\/em>, 2023.<\/li>\n
      7. Quantifying Generative Model Uncertainty in Posterior Sampling Methods for Computational Imaging<\/a>, Canberk Ekmek\u00e7i and M\u00fcjdat \u00c7etin, Conference on Neural Information Processing Systems (NeurIPS), Workshop on Deep Learning and Inverse Problems<\/em>, 2023.<\/li>\n
      8. Analyzing Label Free Leukocyte Trafficking Dynamics on a Microvascular Mimetic with Computer Vision Techniques<\/a>, S. Danial Ahmad, M\u00fcjdat \u00c7etin, Richard E. Waugh, and James L. McGrath, Microphysiological Systems World Summit<\/em>, 2023.<\/li>\n
      9. Estimation of the IOL Position from Clinical OCT 3-D Biometry and Machine Learning Algorithms<\/a>, S. Eduardo Martinez-Enriquez, Yue Zhao, Derick Ansah, U\u011fur \u00c7elik, Scott MacRae, M\u00fcjdat \u00c7etin, and Susana Marcos, Association for Research in Vision and Ophthalmology (ARVO) Annual Meeting<\/em>, 2023.<\/li>\n
      10. Crystalline Lens Geometry from a Clinical OCT-based Biometer as a Function of Age and Refraction<\/a>, Derick Ansah, Eduardo Martinez-Enriquez, Yue Zhao, U\u011fur \u00c7elik, Scott MacRae, M\u00fcjdat \u00c7etin, and Susana Marcos, Association for Research in Vision and Ophthalmology (ARVO) Annual Meeting<\/em>, 2023.<\/li>\n
      11. Adversarial Discriminative Domain Adaptation and Transformers for EEG-based Cross-Subject Emotion Recognition<\/a>, Shadi Sartipi and M\u00fcjdat \u00c7etin, International IEEE EMBS Conference on Neural Engineering<\/em>, 2023.<\/li>\n
      12. Automatic Parameter Tuning for Plug-and-Play Algorithms Using Generalized Cross Validation and Stein’s Unbiased Risk Estimation for Linear Inverse Problems in Computational Imaging<\/a>, Canberk Ekmek\u00e7i and M\u00fcjdat \u00c7etin, IS&T Electronic Imaging Symposium, Computational Imaging Conference<\/em>, 2023.<\/li>\n
      13. Ultrasound Elasticity Reconstruction with Inaccurate Forward Model using Integrated Data-driven Correction of Data-fidelity Gradient<\/a>, Narges Mohammadi, Marvin M. Doyley, and M\u00fcjdat \u00c7etin, IS&T Electronic Imaging Symposium, Computational Imaging Conference<\/em>, 2023.<\/li>\n
      14. Deep-learning based in situ Ultrasound Thermometry for Thermal Ablation Monitoring<\/a>, Ajay Anand, Ashwin Ramesh, Seungju Yeo, Narges Mohammadi, M\u00fcjdat \u00c7etin, and Diane Dalecki, 183rd Meeting of Acoustical Society of America, The Journal of the Acoustical Society of America 152 (4)<\/em>, A114-A114, 2022.<\/li>\n
      15. Fast Topology Identification from Smooth Graph Signals<\/a>, Seyed Saman Saboksayr, Gonzalo Mateos, and M\u00fcjdat \u00c7etin, Fourth International Balkan Conference on Communications and Networking<\/em>, 2021.<\/li>\n
      16. EEG Emotion Recognition via Graph-based Spatio-Temporal Attention Neural Networks<\/a>, Shadi Sartipi, Mastaneh Torkamani-Azar, and M\u00fcjdat \u00c7etin, International Conference of the IEEE Engineering in Medicine and Biology Society<\/em>, 2021.<\/li>\n
      17. What Does Your Computational Imaging Algorithm Not Know?: A Plug-and-Play Model Quantifying Model Uncertainty<\/a>, Canberk Ekmek\u00e7i and M\u00fcjdat \u00c7etin, International Conference on Computer Vision, Learning for Computational Imaging Workshop<\/em>, 2021.<\/li>\n
      18. Combining Physics-based Modeling and Deep Learning for Ultrasound Elastography<\/a>, Narges Mohammadi, Marvin M. Doyley, and M\u00fcjdat \u00c7etin, IEEE International Ultrasonics Symposium<\/em>, 2021.<\/li>\n
      19. Regularization by Adversarial Learning for Ultrasound Elasticity Imaging<\/a>, Narges Mohammadi, Marvin M. Doyley, and M\u00fcjdat \u00c7etin, European Signal Processing Conference<\/em>, 2021.<\/li>\n
      20. Online Graph Learning under Smoothness Priors<\/a>, Seyed Saman Saboksayr, Gonzalo Mateos, and M\u00fcjdat \u00c7etin, European Signal Processing Conference<\/em>, 2021.<\/li>\n
      21. MR Elasticity Reconstruction using Statistical Physical Modeling and Explicit Data-driven Denoising Regularizer<\/a>, Narges Mohammadi, Marvin M. Doyley, and M\u00fcjdat \u00c7etin, IEEE Statistical Signal Processing Workshop<\/em>, 2021.<\/li>\n
      22. Ultrasound Elasticity Imaging using Physics-based Models and Learning-based Plug-and-Play Priors<\/a>, Narges Mohammadi, Marvin M. Doyley, and M\u00fcjdat \u00c7etin, IEEE International Conference on Acoustics, Speech and Signal Processing<\/em>, 2021.<\/li>\n
      23. EEG-based Emotion Classification using Graph Signal Processing<\/a>, Seyed Saman Saboksayr, Gonzalo Mateos, and M\u00fcjdat \u00c7etin, IEEE International Conference on Acoustics, Speech and Signal Processing<\/em>, 2021.<\/li>\n
      24. Finite Element Reconstruction of Stiffness Images in MR Elastography using Statistical Physical Forward Modeling and Proximal Optimization Methods<\/a>, Narges Mohammadi, Marvin M. Doyley, and M\u00fcjdat \u00c7etin, IEEE International Symposium on Biomedical Imaging<\/em>, 2021.<\/li>\n
      25. Model-based Bayesian Deep Learning Architecture for Linear Inverse Problems in Computational Imaging<\/a>, Canberk Ekmek\u00e7i and M\u00fcjdat \u00c7etin, IS&T Electronic Imaging Symposium, Computational Imaging Conference<\/em>, 2021.<\/li>\n
      26. A Statistical Framework for Model-based Inverse Problems in Ultrasound Elastography<\/a>, Narges Mohammadi, Marvin M. Doyley, and M\u00fcjdat \u00c7etin, Asilomar Conference on Signals, Systems, and Computers<\/em>, 2020.<\/li>\n
      27. Compressed Sensing Structured Illumination Microscopy<\/a>, Baturay \u00d6zg\u00fcr\u00fcn and M\u00fcjdat \u00c7etin, IEEE International Engineering in Medicine and Biology Conference<\/em>, 2020.<\/li>\n
      28. Prediction of Motor Imagery Performance based on Pre-Trial Spatio-Spectral Alertness Features<\/a>, Mastaneh Torkamani-Azar, Aysa Jafarifarmand, and M\u00fcjdat \u00c7etin, IEEE International Engineering in Medicine and Biology Conference<\/em>, 2020.<\/li>\n
      29. Interdisciplinary Graduate Training in the Science, Technology, and Applications of Augmented and Virtual Reality<\/a>, M\u00fcjdat \u00c7etin, 4th Annual Frameless Symposium<\/em>, 2019.<\/li>\n
      30. Neural Signatures of Motor Skill in the Resting Brain<\/a>, Ozan \u00d6zdenizci, Timm Meyer, Felix Wichmann, Jan Peters, Bernhard Sch\u00f6lkopf, M\u00fcjdat \u00c7etin, and Moritz Grosse-Wentrup, IEEE International Conference on Systems, Man, and Cybernetics<\/em>, 2019.<\/li>\n
      31. Prediction of Response Time and Vigilance Score in a Sustained Attention Task from Pre-trial Phase Synchrony using Deep Neural Networks<\/a>, Mastaneh Torkamani-Azar, S\u00fcmeyra Demir Kan\u0131k, Sara Atito Ali Ahmed, and M\u00fcjdat \u00c7etin, IEEE International Engineering in Medicine and Biology Conference<\/em>, 2019.<\/li>\n
      32. A Novel Plug-and-Play SAR Reconstruction Framework Using Deep Priors<\/a>, Muhammed Burak Alver, Ammar Saleem, and M\u00fcjdat \u00c7etin, IEEE Radar Conference<\/em>, 2019.<\/li>\n
      33. Simulating Compressive Three-Dimensional Structured Illumination Microscopy<\/a>, Baturay \u00d6zg\u00fcr\u00fcn and M\u00fcjdat \u00c7etin, Optics & Photonics International Congress<\/em>, 2019.<\/li>\n
      34. Compressed Sensing for Structured Illumination Microscopy<\/a>, Baturay \u00d6zg\u00fcr\u00fcn and M\u00fcjdat \u00c7etin, Focus on Microscopy<\/em>, 2019.<\/li>\n
      35. Combining Nonparametric Spatial Context Priors with Nonparametric Shape Priors for Dendritic Spine Segmentation in 2-photon Microscopy Images<\/a>, Ertun\u00e7 Erdil, A. \u00d6zg\u00fcr Argun\u015fah, Tolga Ta\u015fdizen, Devrim \u00dcnay, and M\u00fcjdat \u00c7etin, IEEE International Symposium on Biomedical Imaging<\/em>, 2019.<\/li>\n
      36. Can We Predict Who Will Respond More to Neurofeedback with Resting State EEG?<\/a>, G\u00fcnet Ero\u011flu, Bar\u0131\u015f Ekici, Fehim Arman, Mert G\u00fcrkan, M\u00fcjdat \u00c7etin, and Selim Balc\u0131soy, Medical Technologies Congress<\/em>, 2018.<\/li>\n
      37. SAR ATR in the Phase History Domain using Deep Convolutional Neural Networks<\/a>, Muhammed Burak Alver, Sara Atito, and M\u00fcjdat \u00c7etin, SPIE Remote Sensing Symposium<\/em>, 2018.<\/li>\n
      38. Image Segmentation by Deep Learning of Disjunctive Normal Shape Model Shape Representation<\/a>, Mehran Javanmardi, Ricardo Bigolin Lanfredi, M\u00fcjdat \u00c7etin, and Tolga Ta\u015fdizen, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Workshop on Differential Geometry in Computer Vision and Machine Learning<\/em>, 2017.<\/li>\n
      39. A Subaperture based Approach for SAR Moving Target Imaging by Low-rank and Sparse Decomposition<\/a>, Mubashar Yasin, Ahmed Shaharyar Khwaja, and M\u00fcjdat \u00c7etin, SPIE Defense + Commercial Sensing Symposium<\/em>, 2018.<\/li>\n
      40. Sparse 4D TomoSAR Imaging in the Presence of Non-linear Deformation<\/a>, Ahmed Shaharyar Khwaja and M\u00fcjdat \u00c7etin, SPIE Defense + Commercial Sensing Symposium<\/em>, 2018.<\/li>\n
      41. Sparsity-driven Coupled Imaging and Autofocusing for Interferometric SAR<\/a>, O\u011fuzcan Zengin, Ahmed Shaharyar Khwaja, and M\u00fcjdat \u00c7etin, SPIE Defense + Commercial Sensing Symposium<\/em>, 2018.<\/li>\n
      42. Improving Cognitive Functions of Dyslexics using Multi-sensory Learning and EEG Neurofeedback<\/a>, G\u00fcnet Ero\u011flu, Serap Ayd\u0131n, M\u00fcjdat \u00c7etin, and Selim Balc\u0131soy, IEEE Conference on Signal Processing, Communications, and their Applications, International Workshop on Machine Learning for Understanding the Brain<\/em>, 2018.<\/li>\n
      43. Electroencephalographic Identifiers of Reading Abilities in Turkish Language<\/a>, G\u00fcnet Ero\u011flu, M\u00fcjdat \u00c7etin, and Selim Balc\u0131soy, IEEE Conference on Signal Processing, Communications, and their Applications, International Workshop on Machine Learning for Understanding the Brain<\/em>, 2018.<\/li>\n
      44. “Image Segmentation with Pseudo-marginal MCMC Sampling and Nonparametric Shape Priors<\/a>“, Ertunc Erdil, Sinan Y\u0131ld\u0131r\u0131m, Tolga Tasdizen, and M\u00fcjdat \u00c7etin, Neural Information Processing Systems (NIPS), Advances in Approximate Bayesian Inference Workshop<\/em> 2017.<\/li>\n
      45. “Correlations of Motor Adaptation Learning and Modulation of Resting-State\u00a0Sensorimotor EEG Activity<\/a>“, Ozan \u00d6zdenizci, Mustafa Yal\u00e7\u0131n, Ahmetcan Erdo\u011fan, Volkan Pato\u011flu, Moritz Grosse-Wentrup, and M\u00fcjdat \u00c7etin,\u00a0Graz Brain-Computer Interface Conference,<\/em> 2017.<\/li>\n
      46. “SAR Imaging of Moving Targets by Subaperture based Low-rank and Sparse Decomposition<\/a>“, Mubashar Yasin, Mujdat Cetin and Ahmed Shaharyar Khwaja, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> 2017.<\/li>\n
      47. “Retail Product Recognition with a Graphical Shelf Model<\/a>“, \u0130pek Baz, Erdem Yoruk, Mujdat Cetin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> 2017.<\/li>\n
      48. “3D Dendritic Spine Segmentation using Nonparametric Shape Priors<\/a>“, Erdem Bocugoz, Ertunc Erdil, A. Ozgur Argunsah, Devrim Unay, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> 2017.<\/li>\n
      49. “On Comparison of Different Classification Techniques for the Fine-Grained Retail Product Recognition Problem<\/a>“, O. Berk Satir, \u0130pek Baz, Ertunc Erdil, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> 2017.<\/li>\n
      50. “A Markov Chain Monte Carlo based Rigid Image Registration Method<\/a>“, Navdar Karabulut, Ertunc Erdil, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> 2017.<\/li>\n
      51. “Coupled Shape Priors for Dynamic Segmentation of Dendritic Spines<\/a>“, Naeimeh Atabaki, Ertunc Erdil, A. Ozgur Argunsah, Lavdie Rada, Devrim Unay, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications, International Workshop on Machine Learning for Understanding the Brain,<\/em> 2017.<\/li>\n
      52. “Autofocused Compressive SAR Imaging based\u00a0on the Alternating Direction Method of Multipliers<\/a>“, Alper G\u00fcng\u00f6r, M\u00fcjdat \u00c7etin,\u00a0and H. Emre G\u00fcven,\u00a0\u00a0IEEE Radar Conference,<\/em> 2017.<\/li>\n
      53. “Pre-Movement Contralateral EEG Low Beta Power is Modulated with Motor Adaptation Learning<\/a>“, Ozan \u00d6zdenizci, Mustafa Yal\u00e7\u0131n, Ahmetcan Erdo\u011fan, Volkan Pato\u011flu, Moritz Grosse-Wentrup, and M\u00fcjdat \u00c7etin, IEEE International Conference on Acoustics, Speech, and Signal Processing<\/em>, 2017.<\/li>\n
      54. “Disjunctive Normal Shape Boltzmann Machine<\/a>,” Ertun\u00e7 Erdil, Fitsum Mesadi, Tolga Ta\u015fdizen, and M\u00fcjdat \u00c7etin, IEEE International Conference on Acoustics, Speech, and Signal Processing, 2017.<\/li>\n
      55. “Dendritic Spine Shape Analysis: A Clustering Perspective<\/a>,” M. Usman Ghani, Ertun\u00e7 Erdil, S\u00fcmeyra Demir Kan\u0131k, A. Ozg\u00fcr Argun\u015fah, Anna Felicity Hobbiss, Inbal Israely, Devrim Unay, Tolga Ta\u015fdizen, and M\u00fcjdat \u00c7etin, European Conference on Computer Vision, BioImage Computing Workshop,<\/em> 2016.<\/li>\n
      56. “Disjunctive Normal Level Set: An Efficient Parametric Implicit Method<\/a>,” Fitsum Mesadi, M\u00fcjdat \u00c7etin, and Tolga Ta\u015fdizen, IEEE International Conference on Image Processing,<\/em> 2016.<\/li>\n
      57. “Context-Aware Hybrid Classification System for Fine-Grained Retail Product Recognition<\/a>,” \u0130pek Baz, Erdem Y\u00f6r\u00fck, and M\u00fcjdat \u00c7etin, IEEE Image, Video, and Multidimensional Signal Processing Workshop,<\/em> 2016.<\/li>\n
      58. “MCMC Shape Sampling for Image Segmentation with Nonparametric Shape Priors<\/a>,” Ertun\u00e7 Erdil, Tolga Ta\u015fdizen, and M\u00fcjdat \u00c7etin, IEEE Conference on Computer Vision and Pattern Recognition (CVPR),<\/em> 2016.<\/li>\n
      59. “Resting-State EEG Correlates of Motor Learning Performance in a Force-Field Adaptation Task<\/a>,” Ozan Ozdenizci, Mustafa Yal\u00e7\u0131n, Ahmetcan Erdo\u011fan, Volkan Pato\u011flu, Moritz Grosse-Wentrup, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications, International Workshop on Machine Learning for Understanding the Brain,<\/em> 2016.<\/li>\n
      60. “Classification of Motor Task Execution Speed from EEG Data<\/a>,” Sezen Ya\u011fmur G\u00fcnay, Elif Hocao\u011flu, Volkan Pato\u011flu, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications, International Workshop on Machine Learning for Understanding the Brain,<\/em> 2016.<\/li>\n
      61. “Disjunctive Normal Unsupervised LDA for P300-based Brain-Computer Interfaces<\/a>,” Majed Elwardy, Tolga Ta\u015fdizen, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications, International Workshop on Machine Learning for Understanding the Brain,<\/em> 2016.<\/li>\n
      62. “Dendritic Spine Classification based on Two-Photon Microscopic Images using Sparse Representation<\/a>,” M. Usman Ghani, S\u00fcmeyra Demir Kan\u0131k, A. Ozg\u00fcr Argun\u015fah, Inbal Israely, Devrim \u00dcnay, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> 2016 (in Turkish).<\/li>\n
      63. “Detection of Motor Task Difficulty Level from EEG Data<\/a>,” Sezen Ya\u011fmur G\u00fcnay, Elif Hocao\u011flu, Volkan Pato\u011flu, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> 2016 (in Turkish).<\/li>\n
      64. “Joint Nonparametric Shape and Feature Density Estimation for Segmentation of Dendritic Spines<\/a>,” Ertun\u00e7 Erdil, Lavdie Rada, A. Ozg\u00fcr Argun\u015fah, Inbal Israely, Devrim \u00dcnay, Tolga Ta\u015fdizen, and M\u00fcjdat \u00c7etin, IEEE International Symposium on Biomedical Imaging,<\/em> 2016.<\/li>\n
      65. “Dendritic Spine Shape Analysis Using Disjunctive Normal Shape Models<\/a>,” M. Usman Ghani, Fitsum Mesadi, S\u00fcmeyra Demir Kan\u0131k, A. Ozg\u00fcr Argun\u015fah, Inbal Israely, Devrim Unay, Tolga Ta\u015fdizen, and M\u00fcjdat \u00c7etin, IEEE International Symposium on Biomedical Imaging,<\/em> 2016.<\/li>\n
      66. “On Comparison of Manifold Learning Techniques for Dendritic Spine Classification<\/a>,” M. Usman Ghani, A. Ozg\u00fcr Argun\u015fah, Inbal Israely, Devrim \u00dcnay, Tolga Ta\u015fdizen, and M\u00fcjdat \u00c7etin, IEEE International Symposium on Biomedical Imaging,<\/em> 2016.<\/li>\n
      67. “Disjunctive Normal Shape and Appearance Priors with Applications to Image Segmentation<\/a>,” Fitsum Mesadi, M\u00fcjdat \u00c7etin, and Tolga Ta\u015fdizen, International Conference on Medical Image Computing and Computer Assisted Interventions,<\/em> 2015.<\/li>\n
      68. “An Augmented Lagrangian Method for Image Reconstruction with Multiple Features<\/a>,” H. Emre G\u00fcven, Alper G\u00fcng\u00f6r, and M\u00fcjdat \u00c7etin, IEEE International Conference on Image Processing,<\/em> 2015.<\/li>\n
      69. “Design and Comparative Evaluation of a BCI-based Upper Extremity Robotic Rehabilitation Protocol<\/a>,” Ela Koya\u015f, Mine Sara\u00e7, M\u00fcjdat \u00c7etin, and Volkan Pato\u011flu, IEEE International Conference on Rehabilitation Robotics,<\/em> 2015.<\/li>\n
      70. “An Augmented Lagrangian Method for Autofocused Compressed SAR Imaging<\/a>,” Alper G\u00fcng\u00f6r, M\u00fcjdat \u00c7etin, and H. Emre G\u00fcven, International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing,<\/em> 2015.<\/li>\n
      71. “Low-rank Sparse Matrix Decomposition for Sparsity-driven SAR Image Reconstruction<\/a>,” Abdurrahim So\u011fanl\u0131 and M\u00fcjdat \u00c7etin, International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing,<\/em> 2015.<\/li>\n
      72. “Dendritic Spine Shape Classification from Two-Photon Microscopy Images<\/a>,” Usman Ghani, Sumeyra Demir Kan\u0131k, A. Ozg\u00fcr Argun\u015fah, Tolga Ta\u015fdizen, Devrim \u00dcnay, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> 2015 (in Turkish).<\/li>\n
      73. “Adaptive Neurofeedback on Parieto-Occipital Cortex for Motor Learning Performance<\/a>,” Ozan Ozdenizci, Timm Meyer, M\u00fcjdat \u00c7etin, and Moritz Grosse-Wentrup, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> 2015 (in Turkish).<\/li>\n
      74. “Sparsity-driven SAR Image Reconstruction via Low-rank Sparse Matrix Decomposition<\/a>,” Abdurrahim So\u011fanl\u0131 and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> 2015 (in Turkish).<\/li>\n
      75. “Semi-supervised Adaptation of Motor Imagery Based BCI Systems<\/a>,” Ismail Y\u0131lmaz, Sumeyra Demir Kan\u0131k, Tolga Ta\u015fdizen, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> 2015 (in Turkish).<\/li>\n
      76. “Automated Dendritic Spine Tracking on 2-Photon Microscopic Images<\/a>,” Bike K\u0131l\u0131\u00e7, Lavdie Rada, Ertun\u00e7 Erdil, A. Ozg\u00fcr Argun\u015fah, M\u00fcjdat \u00c7etin, and Devrim \u00dcnay, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> 2015 (in Turkish).<\/li>\n
      77. “Information-Theoretic Noisy Band Detection in Hyperspectral Imagery<\/a>,” Mustafa Erg\u00fcl, Fatih Nar, Emre Aky\u0131lmaz, Nigar \u015een, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> 2015 (in Turkish).<\/li>\n
      78. “Disjunctive Normal Shape Models<\/a>,” Nisha Ramesh, Fitsum Mesadi, M\u00fcjdat \u00c7etin, and Tolga Ta\u015fdizen, IEEE International Symposium on Biomedical Imaging,<\/em> 2015.<\/li>\n
      79. “A Joint Classification and Segmentation Approach for Dendritic Spine Segmentation in 2-Photon Microscopy Images<\/a>,” Ertun\u00e7 Erdil, A. Ozg\u00fcr Argun\u015fah, Tolga Ta\u015fdizen, Devrim \u00dcnay, and M\u00fcjdat \u00c7etin, IEEE International Symposium on Biomedical Imaging,<\/em> 2015.<\/li>\n
      80. “Dictionary Learning for Sparsity-driven SAR Image Reconstruction<\/a>,” Abdurrahim So\u011fanl\u0131 and M\u00fcjdat \u00c7etin, IEEE International Conference on Image Processing,<\/em> 2014.<\/li>\n
      81. “Automatic Dendritic Spine Detection using Multiscale Dot Enhancement Filters and SIFT Features<\/a>,” Lavdie Rada, Ertun\u00e7 Erdil, A. Ozg\u00fcr Argun\u015fah, Devrim \u00dcnay, and M\u00fcjdat \u00c7etin, IEEE International Conference on Image Processing,<\/em> 2014.<\/li>\n
      82. “Towards Neurofeedback Training of Associative Brain Areas for Stroke Rehabilitation<\/a>,” Ozan Ozdenizci, Timm Meyer, M\u00fcjdat \u00c7etin, and Moritz Grosse-Wentrup, International Brain-Computer Interface Conference,<\/em> 2014.<\/li>\n
      83. “A Probabilistic Graphical Model for Word-Level Language Modeling in P300 Spellers<\/a>,” Jaime Fernando Delgado Saa, Adriana de Pesters, Dennis McFarland, and M\u00fcjdat \u00c7etin, International Brain-Computer Interface Conference,<\/em> 2014.<\/li>\n
      84. “An Augmented Lagrangian Method for Sparse SAR Imaging<\/a>,” H. Emre Guven and M\u00fcjdat \u00c7etin, European Conference on Synthetic Aperture Radar,<\/em> 2014 (Invited Paper).<\/li>\n
      85. “SpineS: A Tool for Automatic Determination of the Temporal Volume Change of Dendritic Spines in 2-Photon Microscopy Imagery<\/a>,” Ertun\u00e7 Erdil, A. Ozg\u00fcr Argun\u015fah, Devrim \u00dcnay, and M\u00fcjdat \u00c7etin, National Neuroscience Congress,<\/em> 2014 (in Turkish).<\/li>\n
      86. “An Accelerated Augmented Lagrangian Method with application to Compressed Sensing SAR Imaging<\/a>,” H. Emre G\u00fcven and M\u00fcjdat \u00c7etin, NATO SET-213 Specialist Meeting on Compressive Sensing for Radar\/SAR and EO\/IR Imaging,<\/em> 2014.<\/li>\n
      87. “Dictionary Learning-based Approach for SAR Image Reconstruction<\/a>,” Abdurrahim So\u011fanl\u0131 and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Trabzon, Turkey, April 2014 (in Turkish).<\/li>\n
      88. “Detection of Task Difficulty From Intention Level Information in the EEG Features<\/a>,” Ela Koya\u015f, Elif Hocao\u011flu, M\u00fcjdat \u00c7etin, and Volkan Pato\u011flu, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Trabzon, Turkey, April 2014 (in Turkish).<\/li>\n
      89. “An Alternating Direction Method of Multipliers for Sparse SAR Imaging<\/a>,” H. Emre G\u00fcven and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Trabzon, Turkey, April 2014 (in Turkish).<\/li>\n
      90. “A Robust Nonlinear Scale Space Change Detection Approach for SAR Images<\/a>,” Berk Sevilmi\u015f, O. Erman Okman, Fatih Nar, Can Demirkesen, and M\u00fcjdat \u00c7etin, SPIE Remote Sensing Symposium,<\/em> 2013.<\/li>\n
      91. “Detection of Intention Level in Response to Task Difficulty from EEG Signals<\/a>,” Ela Koya\u015f, Elif Hocao\u011flu, Volkan Pato\u011flu, and M\u00fcjdat \u00c7etin, IEEE International Workshop on Machine Learning for Signal Processing,<\/em> 2013 (Invited paper).<\/li>\n
      92. “SAR Moving Target Imaging Using Group Sparsity<\/a>,” Ozben Onhon and M\u00fcjdat \u00c7etin, EURASIP European Signal Processing Conference,<\/em> 2013.<\/li>\n
      93. “A Sparsity-Driven Approach to Multi-camera Tracking in Visual Sensor Networks<\/a>,” Serhan Co\u015far and M\u00fcjdat \u00c7etin, IEEE International Conference on Advanced Video and Signal-based Surveillance, Workshop on Activity Monitoring by Multiple Distributed Sensing,<\/em> 2013.<\/li>\n
      94. “Incorporation of a Language Model into a Brain Computer Interface based Speller through HMMs<\/a>,” \u00c7a\u011fda\u015f Ula\u015f and M\u00fcjdat \u00c7etin, IEEE International Conference on Acoustics, Speech, and Signal Processing,<\/em> 2013.<\/li>\n
      95. “Brain Computer Interface based Robotic Rehabilitation with Online Modification of Task Speed<\/a>,” Mine Sara\u00e7, Ela Koya\u015f, Ahmetcan Erdo\u011fan, Volkan Pato\u011flu, and M\u00fcjdat \u00c7etin, International Conference on Rehabilitation Robotics,<\/em> 2013.<\/li>\n
      96. “The First Brain-Computer Interface Utilizing a Turkish Language Model<\/a>,” \u00c7a\u011fda\u015f Ula\u015f and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Girne, North Cyprus, April 2013 (in Turkish).<\/li>\n
      97. “Control of a BCI-based Upper Limb Rehabilitation System Utilizing Posterior Probabilities<\/a>,” Ela Koya\u015f, Mine Sara\u00e7, Ahmetcan Erdo\u011fan, M\u00fcjdat \u00c7etin, and Volkan Pato\u011flu, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Girne, North Cyprus, April 2013 (in Turkish).<\/li>\n
      98. “A Watershed and Active Contours Based Method for Dendritic Spine Segmentation in 2-Photon Microscopy Images<\/a>,” Ertun\u00e7 Erdil, A. \u00d6zg\u00fcr Argun\u015fah, Devrim \u00dcnay, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Girne, North Cyprus, April 2013 (in Turkish).<\/li>\n
      99. “Biomedical Image Time Series Registration with Particle Filtering<\/a>,” A. Murat Ya\u011fc\u0131 Ertun\u00e7 Erdil, A. \u00d6zg\u00fcr Argun\u015fah, Devrim \u00dcnay, M\u00fcjdat \u00c7etin, Lale Akarun, and Fikret G\u00fcrgen, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Girne, North Cyprus, April 2013 (in Turkish).<\/li>\n
      100. “Interactive Ship Segmentation in SAR Images<\/a>,” Emre Aky\u0131lmaz, Can Demirkesen, Fatih Nar, O. Erman Okman, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Girne, North Cyprus, April 2013 (in Turkish).<\/li>\n
      101. “Automatic and Semi-automatic Extraction of Curvilinear Features from SAR Images<\/a>,” Emre Akyilmaz, O. Erman Okman, Fatih Nar, and M\u00fcjdat \u00c7etin, SPIE Security + Defence Symposium, SAR Image Analysis, Modeling, and Techniques Conference,<\/em> Edinburgh, United Kingdom, September 2012.<\/li>\n
      102. “Region Based Target Detection in Synthetic Aperture Radar Images and its Parallel Implementation<\/a>,” Can Demirkesen, O. Erman Okman, Fatih Nar, and M\u00fcjdat \u00c7etin, Sixth Defense Technologies Conference,<\/em> Ankara, Turkey, June 2012 (in Turkish).<\/li>\n
      103. “Segmentation of Inhomogeneous Foreground and Background Intensity Objects Using a Probability Density Function Based Data Term and Nonparametric Shape Priors<\/a>,” Abdurrahim Soganli and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Mugla, Turkey, April 2012 (in Turkish).<\/li>\n
      104. “Region Based Target Detection Approach for Synthetic Aperture Radar Images and its Parallel Implementation<\/a>,” Fatih Nar, Can Demirkesen, O. Erman Okman, and M\u00fcjdat \u00c7etin, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XIX,<\/em> E. G. Zelnio and F. D. Garber, Eds., Baltimore, Maryland, USA, April 2012.<\/li>\n
      105. “Handling Phase in Sparse Reconstruction for SAR: Imaging, Autofocusing, and Moving Targets<\/a>,” M\u00fcjdat \u00c7etin, Ozben Onhon, and Sadegh Samadi, European Conference on Synthetic Aperture Radar,<\/em> Nuremberg, Germany, April 2012.<\/li>\n
      106. “Feature Preserving SAR Despeckling and its Parallel Implementation with Application to Railway Detection<\/a>,” O. Erman Okman, Fatih Nar, Can Demirkesen, and M\u00fcjdat \u00c7etin, European Conference on Synthetic Aperture Radar,<\/em> Nuremberg, Germany, April 2012.<\/li>\n
      107. “A Group Sparsity-Driven Approach to 3-D Action Recognition<\/a>,” Serhan Cosar and M\u00fcjdat \u00c7etin, IEEE International Conference on Computer Vision, Workshop on Visual Surveillance,<\/em> Barcelona, Spain, November 2011.<\/li>\n
      108. “Sparsity-driven Image Formation and Space-variant Focusing for SAR<\/a>,” Ozben Onhon and M\u00fcjdat \u00c7etin, IEEE International Conference on Image Processing,<\/em> Brussels, Belgium, September 2011.<\/li>\n
      109. “Hidden Conditional Random Fields for Classification of Imaginary Motor Tasks From EEG Data<\/a>,” Jaime Fernando Delgado Saa and M\u00fcjdat \u00c7etin, EURASIP European Signal Processing Conference,<\/em>
        \nBarcelona, Spain, August 2011.<\/li>\n
      110. “SAR Moving Target Imaging in a Sparsity-driven Framework<\/a>,” Ozben Onhon and M\u00fcjdat \u00c7etin, SPIE Optics + Photonics Symposium, Wavelets and Sparsity XIV Conference,<\/em> San Diego, California, USA, August 2011.<\/li>\n
      111. “A Region-based Target Detection Method for SAR Images<\/a>,” Fatih Nar, Can Demirkesen, O. Erman Okman, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Antalya, Turkey, April 2011 (in Turkish).<\/li>\n
      112. “Sparsity-driven Spatio-temporal EEG Source Estimation<\/a>,” Ozge Batu and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Antalya, Turkey, April 2011 (in Turkish).<\/li>\n
      113. “A Sparsity-driven Approach for SAR Image Formation and Space-variant Focusing<\/a>,” Ozben Onhon and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Antalya, Turkey, April 2011 (in Turkish).<\/li>\n
      114. “AR-PCA-HMM Approach for Sensorimotor Task Classification in EEG-based Brain-Computer Interfaces<\/a>,” Ali Ozgur Argunsah and M\u00fcjdat \u00c7etin, International Conference on Pattern Recognition,<\/em> Istanbul, Turkey, August 2010.<\/li>\n
      115. “Design, Implementation and Evaluation of a Real-time P300-based Brain-Computer Interface System<\/a>,” Armagan Amcalar and M\u00fcjdat \u00c7etin, International Conference on Pattern Recognition,<\/em> Istanbul, Turkey, August 2010.<\/li>\n
      116. “Discrimination of Moderate and Acute Drowsiness Based on Spontaneous Facial Expressions<\/a>,” Esra Vural, Marian Bartlett, Gwen Littlewort, M\u00fcjdat \u00c7etin, Ayt\u00fcl Er\u00e7il, and Javier Movellan, International Conference on Pattern Recognition,<\/em> Istanbul, Turkey, August 2010.<\/li>\n
      117. “Segmentation of Anatomical Structures in Brain MR Images Using Atlases in FSL – A Quantitative Approach<\/a>,” Octavian Soldea, Ahmet Ekin, Diana F. Soldea, Devrim Unay, M\u00fcjdat \u00c7etin, Ayt\u00fcl Er\u00e7il, Gokhan Uzunbas, Zeynep Firat, and Mutlu Cihangiroglu, International Conference on Pattern Recognition,<\/em> Istanbul, Turkey, August 2010.<\/li>\n
      118. “Sparsity-driven Focused SAR Image Formation<\/a>,” Ozben Onhon and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Diyarbakir, Turkey, April 2010 (in Turkish).<\/li>\n
      119. “A Brain-Computer Interface Algorithm based on Hidden Markov Models and Dimensionality Reduction<\/a>,” Ali Ozgur Argunsah and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Diyarbakir, Turkey, April 2010 (in Turkish).<\/li>\n
      120. “A Brain-Computer Interface System for Online Spelling<\/a>,” Armagan Amcalar and M\u00fcjdat \u00c7etin, IEEE Conference on Signal
        \nProcessing, Communications, and their Applications,<\/em> Diyarbakir, Turkey, April 2010 (in Turkish).<\/li>\n
      121. “Joint Sparsity-Driven Inversion and Model Error Correction for Radar Imaging<\/a>,” Ozben Onhon and M\u00fcjdat \u00c7etin, IEEE International Conference on Acoustics, Speech, and Signal Processing,<\/em> Dallas, Texas, USA, March 2010.<\/li>\n
      122. “Automated X-Ray Image Annotation: Single versus Ensemble of Support Vector Machines<\/a>,” Devrim Unay, Octavian Soldea, Sureyya Ozogur-Akyuz, M\u00fcjdat \u00c7etin, and Ayt\u00fcl Er\u00e7il, European Conference on Digital Libraries (ECDL), Cross-Language Evaluation Forum (CLEF) Workshop,<\/em> Corfu, Greece, September-October 2009.<\/li>\n
      123. “Detection of Eye Blinks from EEG using Hidden Markov Models<\/a>,” Ali Ozgur Argunsah, Baran Curuklu, and M\u00fcjdat \u00c7etin, Swedish Association of Medical Engineering and Physics, Medical Technology Days,,<\/em> Vasteras, Sweden, September 2009.<\/li>\n
      124. “Analysis of EEG Signals for Brain Computer Interface<\/a>,” Jessy Parokaran, Ali Ozgur Argunsah, Baran Curuklu, and M\u00fcjdat \u00c7etin, Swedish Association of Medical Engineering and Physics, Medical Technology Days,,<\/em> Vasteras, Sweden, September 2009.<\/li>\n
      125. “Automatic Annotation of X-ray Images: A Study on Attribute Selection<\/a>, Devrim Unay, Octavian Soldea, Ahmet Ekin, M\u00fcjdat \u00c7etin, and Ayt\u00fcl Er\u00e7il, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Workshop on Medical Content-based Retrieval for Clinical Decision Support,<\/em> London, UK, September 2009.<\/li>\n
      126. “An Efficient Monte Carlo Approach for Optimizing Decentralized Estimation Networks Constrained by Undirected Topologies<\/a>,” Murat Uney and M\u00fcjdat \u00c7etin, IEEE Workshop on Statistical Signal Processing,<\/em> Cardiff, Wales, August-September 2009.<\/li>\n
      127. “An Efficient Monte Carlo Approach for Optimizing Communication-Constrained Decentralized Estimation Networks<\/a>,” Murat Uney and M\u00fcjdat \u00c7etin, EURASIP European Signal Processing Conference,<\/em> Glasgow, Scotland, August 2009.<\/li>\n
      128. “An Efficient Message Passing Algorithm for Multi-Target Tracking<\/a>,” Zhexu (Michael) Chen, Lei Chen, M\u00fcjdat \u00c7etin, and Alan
        \nS. Willsky, International Conference on Information Fusion,<\/em> Seattle, Washington, USA, July 2009.<\/li>\n
      129. “Volumetric Segmentation of Multiple Basal Ganglia Structures using Nonparametric Coupled Shape and Inter-Shape Pose Priors<\/a>,” Gokhan Uzunbas, Octavian Soldea, M\u00fcjdat \u00c7etin, Gozde Unal, Ayt\u00fcl Er\u00e7il, Devrim Unay, Ahmet Ekin, and Zeynep Firat IEEE International Symposium on Biomedical Imaging,<\/em> Boston, Massachusetts, USA, June 2009.<\/li>\n
      130. “Volumetric Segmentation of Multiple Basal Ganglia Structures<\/a>,” Gokhan Uzunbas, Octavian Soldea, M\u00fcjdat \u00c7etin, Gozde Unal, and Ayt\u00fcl Er\u00e7il, and Ahmet Ekin, Israeli Symposium on Computer-Aided Surgery, Medical Robotics, and Medical Imaging,<\/em> Tel Aviv, Israel, May 2009.<\/li>\n
      131. “A Nonquadratic Regularization-based Technique for Joint SAR Imaging and Model Error Correction<\/a>,” Ozben Onhon and M\u00fcjdat \u00c7etin, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XVI,<\/em> E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, April 2009.<\/li>\n
      132. “Compressed sensing of mono-static and multi-static SAR<\/a>,” Ivana Stojanovic, W. Clem Karl, and M\u00fcjdat \u00c7etin, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XVI,<\/em> E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, April 2009.<\/li>\n
      133. “Multiple Feature-Enhanced Synthetic Aperture Radar Imaging<\/a>,” Sadegh Samadi, M\u00fcjdat \u00c7etin, and Mohammad Ali Masnadi-Shirazi,
        \nSPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XVI,<\/em> E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, April 2009.<\/li>\n
      134. “Decentralized Random-Field Estimation Under Communication Constraints<\/a>,” Murat Uney and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Antalya, Turkey, April 2009 (in Turkish).<\/li>\n
      135. “A Nonquadratic Regularization Based Image Reconstruction Technique for SAR Data with Phase Errors<\/a>,” Ozben Onhon and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Antalya, Turkey, April 2009 (in Turkish).<\/li>\n
      136. “Multi-Object Segmentation using Coupled Nonparametric Shape and Relative Pose Priors<\/a>,” Gokhan Uzunbas, Octavian Soldea, M\u00fcjdat \u00c7etin, Gozde Unal, and Ayt\u00fcl Er\u00e7il, Devrim Unay, Ahmet Ekin, and Zeynep Firat IS&T\/SPIE Electronic Imaging, Computational Imaging VII,<\/em> San Jose, California, USA, January 2009.<\/li>\n
      137. “Binary and nonbinary description of hypointensity for search and retrieval of brain MR images<\/a>, Devrim Unay, Xiaojing Chen, Ayt\u00fcl Er\u00e7il, M\u00fcjdat \u00c7etin, Radu Jasinschi, Mark A. van Buchem, and Ahmet Ekin, IS&T\/SPIE Electronic Imaging, Multimedia Content Access: Algorithms and Systems III,<\/em> San Jose, California, USA, January 2009.<\/li>\n
      138. “Sparse Signal Representation for Complex-valued Imaging<\/a>,” Sadegh Samadi, M\u00fcjdat \u00c7etin, and Mohammad Ali Masnadi-Shirazi, IEEE Signal Processing Society 13th DSP Workshop & 5th SPE Workshop,<\/em> Marco Island, Florida, USA, January 2009.<\/li>\n
      139. “Automated Drowsiness Detection For Improved Driving Safety,” Esra Vural, M\u00fcjdat \u00c7etin, Ayt\u00fcl Er\u00e7il, Gwen Littlewort, Marian Bartlett, and Javier Movellan, International Conference on Automotive Technologies,<\/em> Istanbul, Turkey, November 2008.<\/li>\n
      140. “Segmentation of the Evolving Left Ventricle by Learning the Dynamics<\/a>,” Walter Sun, M\u00fcjdat \u00c7etin, Ray Chan, and Alan S. Willsky, IEEE International Symposium on Biomedical Imaging,<\/em> Paris, France, May 2008.<\/li>\n
      141. “Coupled Nonparametric Shape Priors for Segmentation of Multiple Basal Ganglia Structures<\/a>,” Gokhan Uzunbas, M\u00fcjdat \u00c7etin, Gozde Unal, and Ayt\u00fcl Er\u00e7il, IEEE International Symposium on Biomedical Imaging,<\/em> Paris, France, May 2008.<\/li>\n
      142. “Hyper-parameter Selection in Advanced Synthetic Aperture Radar Imaging Algorithms<\/a>,” Ozge Batu and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Aydin, Turkey, April 2008 (in Turkish).<\/li>\n
      143. “Target Localization in Acoustic Sensor Networks Using Factor Graphs<\/a>,” Murat Uney and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Aydin, Turkey, April 2008 (in Turkish).<\/li>\n
      144. “Detecting Driver Drowsiness Using Computer Vision Techniques<\/a>,” Esra Vural, M\u00fcjdat \u00c7etin, Ayt\u00fcl Er\u00e7il, Gwen Littlewort, Marian Bartlett, and Javier Movellan, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Aydin, Turkey, April 2008 (in Turkish).<\/li>\n
      145. “Stereo-based 3D Head Pose Tracking using the Scale Invariant Feature Transform<\/a>,” Batu Akan, M\u00fcjdat \u00c7etin, and Ayt\u00fcl Er\u00e7il, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Aydin, Turkey, April 2008 (in Turkish).<\/li>\n
      146. “Segmentation of Multiple Brain Structures Using Coupled Nonparametric Shape Priors<\/a>,” Gokhan Uzunbas, M\u00fcjdat \u00c7etin, Gozde Unal, and Ayt\u00fcl Er\u00e7il, IEEE Conference on Signal Processing, Communications, and their Applications,<\/em> Aydin, Turkey, April 2008 (in Turkish).<\/li>\n
      147. “Joint space aspect reconstruction of wide-angle SAR exploiting sparsity<\/a>,” Ivana Stojanovic, M\u00fcjdat \u00c7etin, and W. Clem Karl, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XV,<\/em> E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, March 2008.<\/li>\n
      148. “Hyper-parameter Selection in Non-quadratic Regularization-based Radar Image Formation<\/a>,” Ozge Batu and M\u00fcjdat \u00c7etin, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XV,<\/em> E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, March 2008.<\/li>\n
      149. “Drowsy Driver Detection Through Facial Movement Analysis<\/a>,” Esra Vural, M\u00fcjdat \u00c7etin, Ayt\u00fcl Er\u00e7il, Gwen Littlewort, Marian Bartlett, and Javier Movellan, IEEE International Conference on Computer Vision, Human Computer Interaction Workshop,<\/em> Rio de Janeiro, Brazil, October 2007.<\/li>\n
      150. “Graphical Model-based Approaches to Target Tracking in Sensor Networks: An Overview of Some Recent Work and Challenges<\/a>,” Murat Uney and M\u00fcjdat \u00c7etin, IEEE International Symposium on Image and Signal Processing and Analysis,<\/em> Istanbul, Turkey, September 2007.<\/li>\n
      151. “A Robust Facial Feature Point Tracker using Graphical Models<\/a>,” Serhan Cosar, M\u00fcjdat \u00c7etin, and Ayt\u00fcl Er\u00e7il, IEEE International Symposium on Image and Signal Processing and Analysis,<\/em> Istanbul, Turkey, September 2007.<\/li>\n
      152. “Shape and Data-Driven Texture Segmentation using Local Binary Patterns<\/a>,” Erkin Tekeli, M\u00fcjdat \u00c7etin, and Ayt\u00fcl Er\u00e7il, EURASIP European Signal Processing Conference,<\/em> Poznan, Poland, September 2007.<\/li>\n
      153. “Robustness of Local Binary Patterns in Brain MR Image Analysis<\/a>, Devrim Unay, Ahmet Ekin, M\u00fcjdat \u00c7etin, Radu Jasinschi, and Ayt\u00fcl Er\u00e7il, International Conference of the IEEE Engineering in Medicine and Biology Society,<\/em> Lyon, France, August 2007.<\/li>\n
      154. “Graphical Model based Facial Feature Point Tracking in a Vehicle Environment<\/a>,” Serhan Cosar, M\u00fcjdat \u00c7etin, and Ayt\u00fcl Er\u00e7il, Biennial on DSP for in-Vehicle and Mobile Systems,<\/em> Istanbul, Turkey, June 2007.<\/li>\n
      155. “Machine Learning Systems for Detecting Driver Drowsiness<\/a>,” Esra Vural, M\u00fcjdat \u00c7etin, Ayt\u00fcl Er\u00e7il, Gwen Littlewort, Marian Bartlett, and Javier Movellan, Biennial on DSP for in-Vehicle and Mobile Systems,<\/em> Istanbul, Turkey, June 2007.<\/li>\n
      156. “3D Head Tracking using Normal Flow Constraints in a Vehicle Environment<\/a>,” Batu Akan, M\u00fcjdat \u00c7etin, and Ayt\u00fcl Er\u00e7il, Biennial on DSP for in-Vehicle and Mobile Systems,<\/em> Istanbul, Turkey, June 2007.<\/li>\n
      157. “A Sparse Signal Representation-based Approach to Image Formation and Anisotropy Determination in Wide-Angle Radar<\/a>,” Kush R. Varshney, M\u00fcjdat \u00c7etin, John W. Fisher III, and Alan S. Willsky, IEEE Conference on Signal Processing and Communications Applications,<\/em> Eskisehir, Turkey, June 2007 (in Turkish).<\/li>\n
      158. “Non-quadratic Regularization Based Image Deblurring: Automatic Parameter Selection and Feature Based Evaluation)<\/a>,” Ozge Batu and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing and Communications Applications,<\/em> Eskisehir, Turkey, June 2007 (in Turkish).<\/li>\n
      159. “Eye Feature Point Tracking by Using Graphical Models<\/a>,” Serhan Cosar and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing and Communications Applications,<\/em> Eskisehir, Turkey, June 2007 (in Turkish).<\/li>\n
      160. “Factors that Affect Classification Performance in EEG based Brain-Computer Interfaces<\/a>,” Ali Ozgur Argunsah, Ali Baran Curuklu, M\u00fcjdat \u00c7etin, and Ayt\u00fcl Er\u00e7il, IEEE Conference on Signal Processing and Communications Applications,<\/em> Eskisehir, Turkey, June 2007 (in Turkish).<\/li>\n
      161. “A Local Binary Patterns and Shape Priors based Texture Segmentation Method)<\/a>,” Erkin Tekeli, M\u00fcjdat \u00c7etin, and Ayt\u00fcl Er\u00e7il, IEEE Conference on Signal Processing and Communications Applications , <\/em> Eskisehir, Turkey, June 2007 (in Turkish).<\/li>\n
      162. “A Novel Feature Extraction Method for Improving P300-Speller Performance<\/a>,” Ali Ozgur Argunsah, Ali Baran Curuklu, M\u00fcjdat \u00c7etin, and Ayt\u00fcl Er\u00e7il, Applied Neuroscience for Healthy Brain Function Scientific Meeting, <\/em> Nijmegen, The Netherlands, May 2007.<\/li>\n
      163. “Machine Learning Systems for Detecting Driver Drowsiness,” Esra Vural, M\u00fcjdat \u00c7etin, Ayt\u00fcl Er\u00e7il, Marian Bartlett, and Javier Movellan, Workshop for Women in Machine Learning, <\/em> San Diego, California, USA, October 2006.<\/li>\n
      164. “Wide-Angle SAR Image Formation with Migratory Scattering Centers and Regularization in Hough Space<\/a>,” Kush R. Varshney, M\u00fcjdat \u00c7etin, John W. Fisher III, and Alan S. Willsky, Adaptive Sensor Array Processing Workshop,<\/em> Lexington, Massachusetts, June 2006.<\/li>\n
      165. “Sparsity-Driven Sparse-Aperture Ultrasound Imaging<\/a>,” M\u00fcjdat \u00c7etin, Emmanuel Bossy, Robin Cleveland, and W. Clem Karl, IEEE International Conference on Acoustics, Speech, and Signal Processing, <\/em> Toulouse, France, May 2006.<\/li>\n
      166. “Joint Image Formation and Anisotropy Characterization in Wide-Angle SAR<\/a>,” Kush R. Varshney, M\u00fcjdat \u00c7etin, John W. Fisher III, and Alan S. Willsky, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XIII,<\/em> E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, April 2006.<\/li>\n
      167. “Synthetic Aperture Radar Imaging from Wide-Angle Data with Frequency-Band Omissions<\/a>,” M\u00fcjdat \u00c7etin and Randolph L. Moses, IEEE Conference on Signal Processing and Communications Applications, <\/em>Antalya, Turkey, April 2006 (in Turkish).<\/li>\n
      168. “Intrinsic Image Estimation and Image Deblurring for Microscopic Images<\/a>,” Eray Dogan and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing and Communications Applications, <\/em>Antalya, Turkey, April 2006 (in Turkish).<\/li>\n
      169. “A Fast Algorithm for Vision-based Hand Gesture Recognition for Robot Control <\/a>,” Asanterabi Malima, Erol Ozgur, and M\u00fcjdat \u00c7etin, IEEE Conference on Signal Processing and Communications Applications, <\/em>Antalya, Turkey, April 2006.<\/li>\n
      170. “Nonparametric Shape Priors for Active Contour-based Image Segmentation<\/a>,” Junmo Kim, M\u00fcjdat \u00c7etin, and Alan S. Willsky, EURASIP European Signal Processing Conference (EUSIPCO),<\/em> Antalya, Turkey, September 2005.<\/li>\n
      171. “Distributed Data Association for Multi-Target Tracking in Sensor Networks<\/a>,” Lei Chen, M\u00fcjdat \u00c7etin, and Alan S. Willsky, International Conference on Information Fusion,<\/em> Philadelphia, Pennsylvania, July 2005. (Best Student Paper Award)<\/li>\n
      172. “Segmenting and Tracking the Left Ventricle by Learning the Dynamics in Cardiac Images<\/a>,” Walter Sun, M\u00fcjdat \u00c7etin, Ray Chan, Vivek Reddy, Fred Holmvang, Venkat Chandar, and Alan S. Willsky, Information Processing in Medical Imaging,<\/em> Glenwood Springs, Colorado, July 2005.<\/li>\n
      173. “Graphical Model-Based Algorithms for Data Association in Distributed Sensing,” Lei Chen, M\u00fcjdat \u00c7etin, and Alan S. Willsky, Adaptive Sensor Array Processing Workshop,<\/em> Lexington, Massachusetts, June 2005.<\/li>\n
      174. “Collaborative Distributed Inference with Minimal Online Communication<\/a>,” O. Patrick Kreidl, M\u00fcjdat \u00c7etin, and Alan S. Willsky, The Learning Workshop,<\/em> Snowbird, Utah, April 2005.<\/li>\n
      175. “SAR imaging from partial-aperture data with frequency-band omissions<\/a>,” M\u00fcjdat \u00c7etin and Randy L. Moses, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XII,<\/em> E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, March-April 2005.<\/li>\n
      176. “Homotopy Continuation for Sparse Signal Representation<\/a>,” Dmitry M. Malioutov, M\u00fcjdat \u00c7etin, and Alan S. Willsky, IEEE International Conference on Acoustics, Speech, and Signal Processing, <\/em> Philadelphia, Pennsylvania, March 2005.<\/li>\n
      177. “Semi-Blind Sparse Channel Estimation with Constant Modulus Symbols<\/a>,” M\u00fcjdat \u00c7etin and Brian M. Sadler, IEEE International Conference on Acoustics, Speech, and Signal Processing, <\/em> Philadelphia, Pennsylvania, March 2005.<\/li>\n
      178. “A Fast Hybrid Approach for SAR Classification<\/a>,” Brian Huether, Timo Kempf, and M\u00fcjdat \u00c7etin, European Conference on Synthetic Aperture Radar, <\/em> Ulm, Germany, May 2004.<\/li>\n
      179. “Optimal Sparse Representations in General Overcomplete Bases<\/a>,” Dmitry M. Malioutov, M\u00fcjdat \u00c7etin, and Alan S. Willsky, IEEE International Conference on Acoustics, Speech, and Signal Processing, <\/em> vol. 2, pp. 793-796, Montreal, Canada, May 2004.<\/li>\n
      180. “Region-Enhanced Imaging for Sparse-Aperture Passive Radar<\/a>,” M\u00fcjdat \u00c7etin and Aaron Lanterman, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XI,<\/em> E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, April 2004.<\/li>\n
      181. “Wide Angle SAR Imaging<\/a>,” Randy L. Moses, Lee Potter, and M\u00fcjdat \u00c7etin, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XI,<\/em> E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, April 2004.<\/li>\n
      182. “Localization of Oceanic Fronts and Feature Boundaries Using a Variational Technique<\/a>,” Walter Sun, M\u00fcjdat \u00c7etin, W. Carlisle Thacker, T. Mike Chin, and Alan S. Willsky, American Geophysical Union Fall Meeting,<\/em> San Francisco, California, December 2003. (Outstanding Student Paper Award)<\/li>\n
      183. “Data Fusion in Large Arrays of Microsensors<\/a>,” Alan S. Willsky, Dmitry M. Malioutov, and M\u00fcjdat \u00c7etin, Military Sensing Symposia (MSS) Specialty Group on Battlefield Acoustic and Seismic Sensing, Magnetic and Electric Field Sensors Symposium,<\/em> October 2003.<\/li>\n
      184. “Source localization by enforcing sparsity through a Laplacian prior: an SVD-based approach<\/a>,” Dmitry M. Malioutov, M\u00fcjdat \u00c7etin, and Alan S. Willsky, IEEE Statistical Signal Processing Workshop,<\/em> pp. 553-556, St. Louis, Missouri, September-October 2003.<\/li>\n
      185. “Incorporating Complex Statistical Information in Active Contour-based Image Segmentation<\/a>,” Junmo Kim, John W. Fisher III, M\u00fcjdat \u00c7etin, Anthony Yezzi, Jr., and Alan S. Willsky, IEEE International Conference on Image Processing,<\/em> September 2003.<\/li>\n
      186. “A Unified Variational Approach to Denoising and Bias Correction in MR<\/a>,” Ayres Fan, William Wells, John Fisher, M\u00fcjdat \u00c7etin, Steven Haker, Robert Mulkern, Clare Tempany, and Alan S. Willsky, Information Processing in Medical Imaging,<\/em> July 2003.<\/li>\n
      187. “An Edge-Preserving Regularization Method for Coherent Imaging Applications<\/a>,” M\u00fcjdat \u00c7etin, W. Clem Karl, and Alan S. Willsky, IEEE Conference on Signal Processing and Communications Applications, <\/em>Istanbul, Turkey, June 2003 (in Turkish).<\/li>\n
      188. “Multitarget-Multisensor Data Association Using the Tree-Reweighted Max-Product Algorithm<\/a>,” Lei Chen, Martin Wainwright, M\u00fcjdat \u00c7etin, and Alan S. Willsky, SPIE AeroSense Symposium, Signal Processing, Sensor Fusion, and Target Recognition XII,<\/em> I. Kadar, Ed., Proc. SPIE, vol. 5096, pp. 127-138, Orlando, Florida, April 2003.<\/li>\n
      189. “Application of Point Enhancement Technique for Ship Target Recognition by HRR<\/a>,” Nil\u00fcfen \u00c7otuk, Sedat T\u00fcre, and M\u00fcjdat \u00c7etin, SPIE AeroSense Symposium, Algorithms for Synthetic Aperture Radar Imagery X,<\/em> E. G. Zelnio and F. D. Garber, Eds., Proc. SPIE, vol. 5095, pp. 185-193, Orlando, Florida, April 2003.<\/li>\n
      190. “Edge-Preserving Image Reconstruction for Coherent Imaging Applications<\/a>,” M\u00fcjdat \u00c7etin, W. Clem Karl, and Alan S. Willsky, IEEE International Conference on Image Processing,<\/em> vol. 2, pp. 481-484, Rochester, New York,
        \nSeptember 2002.<\/li>\n
      191. “A Curve Evolution-Based Variational Approach to Simultaneous Image Restoration and Segmentation<\/a>,” Junmo Kim, Andy Tsai, M\u00fcjdat \u00c7etin, and Alan S. Willsky, IEEE International Conference on Image Processing, <\/em> vol. 1, pp. 109-112, Rochester, New York, September 2002.<\/li>\n
      192. “Nonparametric Methods for Image Segmentation using Information Theory and Curve Evolution<\/a>,” Junmo Kim, John W. Fisher III, Anthony Yezzi, Jr., M\u00fcjdat \u00c7etin, and Alan S. Willsky, IEEE International Conference on Image Processing,<\/em> vol. 3, pp. 797-800, Rochester, New York, September 2002.<\/li>\n
      193. “Super-resolution source localization through data-adaptive regularization<\/a>,” Dmitry M. Malioutov, M\u00fcjdat \u00c7etin, John W. Fisher III, and Alan S. Willsky, IEEE Sensor Array and Multichannel Signal Processing Workshop,<\/em> pp. 194-198, Rosslyn, Virginia, August 2002.<\/li>\n
      194. “A Variational Technique for Source Localization based on a Sparse Signal Reconstruction Perspective<\/a>,” M\u00fcjdat \u00c7etin, Dmitry M. Malioutov, and Alan S. Willsky, IEEE International Conference on Acoustics, Speech, and Signal Processing, <\/em> vol. 3, pp. 2965-2968, Orlando, Florida, May 2002.<\/li>\n
      195. “Analysis of the Impact of Feature-Enhanced SAR Imaging on ATR Performance<\/a>,” M\u00fcjdat \u00c7etin, W. Clem Karl, and David A. Casta\u00f1on, SPIE AeroSense Symposium, Algorithms for Synthetic Aperture Radar Imagery IX, <\/em>E.G. Zelnio, Ed., Proc. SPIE, vol. 4727, <\/em>pp. 134-145, Orlando, Florida, April 2002.<\/li>\n
      196. “Formation of HRR Profiles by Non-Quadratic Optimization for Improved Feature Extraction<\/a>,” M\u00fcjdat \u00c7etin, W. Clem Karl, and David A. Casta\u00f1on, SPIE AeroSense Symposium, Algorithms for Synthetic Aperture Radar Imagery IX, <\/em>E.G. Zelnio, Ed., Proc. SPIE, vol. 4727, <\/em>pp. 213-224, Orlando, Florida, April 2002.<\/li>\n
      197. “Super-resolution source localization through data-adaptive regularization,” Dmitry M. Malioutov, M\u00fcjdat \u00c7etin, John W. Fisher III, and Alan S. Willsky, Adaptive Sensor Array Processing Workshop,<\/em> Lexington, Massachusetts, March 2002.<\/li>\n
      198. “Complex-valued image reconstruction by half-quadratic regularization,” M\u00fcjdat \u00c7etin and W. Clem Karl, SIAM Conference on Imaging Science,<\/em> Boston, Massachusetts, March 2002.<\/li>\n
      199. “Superresolution and edge-preserving reconstruction of complex-valued synthetic aperture radar images<\/a>,” M\u00fcjdat \u00c7etin and W. Clem Karl, IEEE International Conference on Image Processing, <\/em> vol. 1, pp. 701-704, Vancouver, Canada, September 2000.<\/li>\n
      200. “Enhanced, high resolution radar imaging based on robust regularization<\/a>,” M\u00fcjdat \u00c7etin and W. Clem Karl, IEEE International Conference on Acoustics, Speech, and Signal Processing, <\/em>vol. 4, pp. 2278-2281, Istanbul, Turkey, June 2000.<\/li>\n
      201. “Evaluation of a regularized SAR imaging technique based on recognition-oriented features<\/a>,” M\u00fcjdat \u00c7etin, W. Clem Karl, and David A. Casta\u00f1on, SPIE AeroSense Symposium, Algorithms for Synthetic Aperture Radar Imagery VII, <\/em>E.G. Zelnio, Ed., Proc. SPIE, vol. 4053, <\/em>pp. 40-51, Orlando, Florida, April 2000.<\/li>\n
      202. “Sentetik aciklikli radar ile goruntu gericatilmasina istatistiksel bir yaklasim<\/a>,” M\u00fcjdat \u00c7etin and W. Clem Karl, IEEE Conference on Signal Processing and its Applications, <\/em>Ankara, Turkey, June 1999 (in Turkish).<\/li>\n
      203. “A statistical method for discrimination of natural terrain types from SAR data<\/a>,” M\u00fcjdat \u00c7etin and W. Clem Karl, IEEE International Conference on Image Processing, <\/em>vol. 1, pp. 587-591, Chicago, Illinois, October 1998.<\/li>\n
      204. “A statistical tomographic approach to synthetic aperture radar image reconstruction<\/a>,” M\u00fcjdat \u00c7etin and W. Clem Karl, IEEE International Conference on Image Processing, <\/em>vol. 1, pp. 845-848, Santa Barbara, California, October 1997.<\/li>\n
      205. “Inversion and inference based on tomographic data,” M\u00fcjdat \u00c7etin and W. Clem Karl, Progress in Electromagnetics Research Symposium, <\/em>p. 573, Cambridge, Massachusetts, July 1997.<\/li>\n<\/ol>\n
        \n

        Theses<\/h2>\n
        \n<\/div>\n
          \n
        1. Fazla Mashrur, “Sleep State Analysis based on Multi-Modal Neurophysiological Data,” ongoing.<\/li>\n
        2. Hakki Motorcu, “Computational Imaging and Image Analysis for Light-Sheet Microscopy,” ongoing.<\/li>\n
        3. Canberk Ekmekci, “Bayesian Machine Learning for Computational Imaging,” ongoing.<\/li>\n
        4. Narges Mohammadi, “Machine Learning for Computational Elastographic Imaging,” ongoing.<\/li>\n
        5. Shadi Sartipi, “Affective Brain-Computer Interfaces,” ongoing.<\/li>\n
        6. Ammar Saleem, “Machine Learning Methods for Computational Radar Imaging,” ongoing.<\/li>\n
        7. Muhammed Burak Alver, “Synthetic Aperture Radar Imaging with Deep Neural Networks<\/a>,” December 2020.<\/li>\n
        8. Baturay \u00d6zg\u00fcr\u00fcn, “Compressed Sensing and Learning-Based Methods for Super-Resolution Structured Illumination Microscopy<\/a>,” October 2020.<\/li>\n
        9. Mastaneh Torkamani Azar, “Towards Adaptive Brain-Computer Interfaces: Statistical Inference for Mental State Recognition<\/a>,” August 2020.<\/li>\n
        10. Gunet Eroglu, “Improving Reading Abilities in Dyslexia with Neurofeedback and Multi-Sensory Learning<\/a>,” June 2020.<\/li>\n
        11. \u0130pek Baz, “Statistical Methods for Fine-Grained Retail Product Recognition<\/a>,” August 2019.<\/li>\n
        12. Ertun\u00e7 Erdil, “Bayesian Methods for Segmentation of Objects from Multimodal and Complex Shape Densities using Statistical Shape Priors<\/a>,” January 2018.<\/li>\n
        13. O\u011fuzcan Zengin, “Sparsity-driven Coupled Imaging and Autofocusing for Interferometric SAR<\/a>,” 2018.<\/li>\n
        14. Naeimeh Atabakilachini, “Non-parametric Coupled Shape Priors for Segmentation of Deformable Objects in Time-series Images using Particle Filters<\/a>,” 2018.<\/li>\n
        15. Mubashar Yasin, “SAR Imaging of Moving Targets by Subaperture Based Low-Rank and Sparse Decomposition<\/a>,” 2017.<\/li>\n
        16. Majed Elwardy, “Disjunctive Normal Unsupervised LDA for P300-based Brain-Computer Interfaces<\/a>,” 2016.<\/li>\n
        17. Abdullahi Adamu, “Analysis of Error-Related Potentials in P300 and Motor Imagery Based Brain Computer Interfaces<\/a>,” 2016.<\/li>\n
        18. Sezen Ya\u011fmur G\u00fcnay, “Decoding of Motor Task Difficulty and Execution Speed from EEG Data with Application to Stroke Rehabilitation<\/a>,” 2016.<\/li>\n
        19. Ozan Ozdenizci, “Identifying Neural Correlates of Motor Adaptation Learning for BCI-Assisted Stroke Rehabilitation<\/a>,” 2016.<\/li>\n
        20. M. Usman Ghani, “Dendritic Spine Shape Analysis based on Two-Photon Microscopy Images<\/a>,” 2016.<\/li>\n
        21. Ismail Y\u0131lmaz, “Adaptation in P300 and Motor Imagery-based BCI Systems<\/a>,” September 2015.<\/li>\n
        22. Jaime Fernando Delgado Saa, “Probabilistic Graphical Models for Brain-Computer Interfaces<\/a>,” January 2014.<\/li>\n
        23. Abdurrahim So\u011fanl\u0131, “Dictionary Learning and Low-rank Sparse Matrix Decomposition for Sparsity-driven SAR Image Reconstruction<\/a>,” September 2014.<\/li>\n
        24. Serhan Co\u015far, “Sparse Representation Frameworks for Inference Problems in Visual Sensor Networks<\/a>,” November 2013.<\/li>\n
        25. Ela Koya\u015f, “Design and Analysis of a Brain-Computer Interface-based Robotic Rehabilitation System<\/a>,” November 2013.<\/li>\n
        26. \u00c7a\u011fda\u015f Ula\u015f, “Incorporation of a Language Models into a Brain-Computer Interface-based Speller<\/a>,” September 2013.<\/li>\n
        27. Hamza Fawzi Altakroury, “Error Detection and New Stimulus Mechanisms in Brain-Computer Interfaces<\/a>,” June 2013.<\/li>\n
        28. Ozben \u00d6nhon, “Joint Sparsity-Driven Inversion and Model Error Correction for SAR Imaging<\/a>,” February 2012.<\/li>\n
        29. Adrian Aycan Corum, “Fast Algorithms for Smooth and Monotone Covariance Matrix Estimation<\/a>,” August 2012.<\/li>\n
        30. Ali \u00d6zg\u00fcr Argun\u015fah, “An HMM-PCA Approach for EEG-Based Brain-Computer Interfaces<\/a>,” March 2010.<\/li>\n
        31. Arma\u011fan Amcalar, “Design, Implementation and Evaluation of a Real-time P300-based Brain-Computer Interface System<\/a>,” February 2010.<\/li>\n
        32. Murat Uney, “Decentralized Estimation under Communication Constraints<\/a>,” October 2009.<\/li>\n
        33. Esra Vural, “Video Based Detection of Driver Fatigue<\/a>,” August 2009<\/li>\n
        34. Ozge Batu, “Parameter Selection in Non-quadratic Regularization-based SAR Imaging<\/a>,” August 2008.<\/li>\n
        35. G\u00f6khan Uzunba\u015f, “Coupled Non-parametric Shape and Moment-based Inter-shape Pose Priors for Multiple Basal Ganglia Structure Segmentation<\/a>,” August 2008.<\/li>\n
        36. Serhan Co\u015far, “Facial Feature Point Tracking based on a Graphical Model Framework<\/a>,” January 2008.<\/li>\n
        37. Batu Akan, “Stereo-based 3D Head Pose Tracking Using the Scale Invariant Feature Transform<\/a>,” January 2008.<\/li>\n
        38. Erkin Tekeli, “Shape and Data Driven Texture Segmentation using Local Binary Patterns<\/a>,” February 2007.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

          Journal Papers LG-Sleep: Local and Global Temporal Dependencies for Mice Sleep Scoring, Shadi Sartipi, Mie Andersen, Natalie Hauglund, Celia Kj\u00e6rby, Verena Untiet, Maiken Nedergaard, and M\u00fcjdat \u00c7etin, Springer Biomedical Engineering…<\/p>\n","protected":false},"author":12,"featured_media":0,"parent":1502,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-2872","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/sites.rochester.edu\/sdis\/wp-json\/wp\/v2\/pages\/2872","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.rochester.edu\/sdis\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.rochester.edu\/sdis\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.rochester.edu\/sdis\/wp-json\/wp\/v2\/users\/12"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.rochester.edu\/sdis\/wp-json\/wp\/v2\/comments?post=2872"}],"version-history":[{"count":35,"href":"https:\/\/sites.rochester.edu\/sdis\/wp-json\/wp\/v2\/pages\/2872\/revisions"}],"predecessor-version":[{"id":6972,"href":"https:\/\/sites.rochester.edu\/sdis\/wp-json\/wp\/v2\/pages\/2872\/revisions\/6972"}],"up":[{"embeddable":true,"href":"https:\/\/sites.rochester.edu\/sdis\/wp-json\/wp\/v2\/pages\/1502"}],"wp:attachment":[{"href":"https:\/\/sites.rochester.edu\/sdis\/wp-json\/wp\/v2\/media?parent=2872"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}