Publications

    Journal Papers

  1. “SAR Moving Object Imaging Using Sparsity Imposing Priors,” Özben Önhon and Müjdat Çetin, EURASIP Journal on Advances in Signal Processing, special issue on Advanced Techniques for Radar Signal Processing, to appear.
  2. “Dendritic Spine Classification using Shape and Appearance Features based on Two-Photon Microscopy,” M. Usman Ghani, Fitsum Mesadi, SÜmeyra Demir Kanık, A. Özgür Argunşah, Anna Felicity Hobbiss, Inbal Israely, Devrim Ünay, Tolga Taşdizen, and Müjdat Çetin, Journal of Neuroscience Methods, to appear.
  3. Sparse Representation-based Algorithm for Joint SAR Image Formation and Autofocus,” Mohammad Javad Hasankhaan, Sadegh Samadi, and Müjdat Çetin, Signal, Image and Video Processing, 2016.
  4. Recursive Bayesian Coding for BCIs,” Matt Higger, Fernando Quivira, Murat Akcakaya, Mohammad Moghadamfalahi, Hooman Nezamfar, Müjdat Çetin, and Deniz Erdogmus IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2016.
  5. An Augmented Lagrangian Method for Complex-Valued Compressed SAR Imaging,” H. Emre Güven, Alper Güngör, and Müjdat Çetin, IEEE Transactions on Computational Imaging, vol. 2, no. 3, pp. 235-250, September 2016.
  6. Covariance Matrix Estimation for Interest-Rate Risk Modeling via Smooth and Monotone Regularization,” Dmitry M. Malioutov, Aycan A. Corum, and Müjdat Çetin, IEEE Journal of Selected Topics in Signal Processing, vol. 10, no. 6, pp. 1006-1014, September 2016.
  7. Asynchronous Decoding of Finger Movements from ECoG Signals using Long-Range Dependencies through Conditional Random Fields,” Jaime Fernando Delgado Saa, Adriana de Pesters, and Müjdat Çetin, Journal of Neural Engineering, vol. 13, no. 3, p. 036017, June 2016.
  8. Sparsity-Driven Bandwidth-Efficient Decentralized Tracking in Visual Sensor Networks,”
    Serhan Cosar and Müjdat Çetin, Computer Vision and Image Understanding, vol. 139, pp. 40-58, October 2015.
  9. On the Quality and Timeliness of Fusion in a Random Access Sensor Network,” Abdurrahim Soganli, Ozgur Ercetin, and Müjdat Çetin, IEEE Signal Processing Letters, vol. 22, no. 9, pp. 1259-1263, September 2015.
  10. Word-level Language Modeling for P300 Spellers based on Discriminative Graphical Models,” Jaime Fernando Delgado Saa, Adriana de Pesters, Dennis McFarland, and Müjdat Çetin, Journal of Neural Engineering, vol. 12, no. 2, p. 026007, April 2015.
  11. Optimization of Decentralized Random Field Estimation Networks under Communication Constraints through Monte Carlo Methods,” Murat Uney and Müjdat Çetin, Digital Signal Processing, vol. 34, pp. 16-28, November 2014.
  12. Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, Autofocusing, Moving Targets, and Compressed Sensing ,” Müjdat Çetin, Ivana Stojanovic, N. Ozben Onhon, Kush R. Varshney, Sadegh Samadi, W. Clem Karl, and Alan S. Willsky, IEEE Signal Processing Magazine, vol. 31, no. 4, pp. 27-40, July 2014.
  13. Feature Compression: A Framework for Multi-View Multi-Person Tracking in Visual Sensor Networks,” Serhan Cosar and Müjdat Çetin, Journal of Visual Communication and Image Representation, vol. 25, no. 5, pp. 864-873, July 2014.
  14. Combining Learning-based Intensity Distributions with Nonparametric Shape Priors for Image Segmentation,” Abdurrahim Soganli, Gokhan Uzunbas, and Müjdat Çetin, Springer Signal, Image and Video Processing, vol. 8, no. 4, pp. 789-798, May 2014.
  15. Compressed Sensing of Monostatic and Multistatic SAR,” Ivana Stojanovic, Müjdat Çetin, and W. Clem Karl, IEEE Geoscience and Remote Sensing Letters, vol. 10, no. 6, pp. 1444-1448, November 2013.
  16. Discriminative Methods for Classification of Asynchronous Imaginary Motor Tasks From EEG Data,” Jaime Fernando Delgado Saa and Müjdat Çetin, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 21, no. 5, pp. 716-724, September 2013.
  17. Multiple Feature-Enhanced SAR Imaging using Sparsity in Combined Dictionaries,” Sadegh Samadi, Müjdat Çetin, and Mohammad Ali Masnadi-Shirazi, IEEE Geoscience and Remote Sensing Letters, vol. 10, no. 4, pp. 821-825, July 2013.
  18. A Latent Discriminative Model-Based Approach for Classification of Imaginary Motor Tasks from EEG Data,” Jaime Fernando Delgado Saa and Müjdat Çetin, Journal of Neural Engineering, 9, 026020, 2012.
  19. A Sparsity-driven Approach for Joint SAR Imaging and Phase Error Correction,” Ozben Onhon and Müjdat Çetin, IEEE Trans. Image Processing, vol. 21, no. 4, pp. 2075-2088, April 2012.
  20. Sparsity-driven Ultrasound Imaging,” Ahmet Tuysuzoglu, Jonathan M. Kracht, Müjdat Çetin, Robin Cleveland, and W. Clem Karl, Journal of the Acoustical Society of America, vol. 131, no.2, pp. 1271-1281, February 2012.
  21. Monte Carlo Optimization of Decentralized Estimation Networks Over Directed Acyclic Graphs Under Communication Constraints,” Murat Uney and Müjdat Çetin, IEEE Trans. Signal Processing, vol. 59, no. 11, pp. 5558-5576, November 2011.
  22. Parameter Selection in Sparsity-driven SAR Imaging,” Ozge Batu and Müjdat Çetin, IEEE Trans. Aerospace and Electronic Systems, vol. 47, no. 4, pp. 3040-3050, October 2011.
  23. A Graphical Model based Solution to the Facial Feature Point Tracking Problem,” Serhan Cosar and Müjdat Çetin, Image and Vision Computing, vol. 29, no. 5, pp. 335-350, April 2011.
  24. Sparse Representation-Based Synthetic Aperture Radar Imaging,” Sadegh Samadi, Müjdat Çetin, and Mohammad Ali Masnadi-Shirazi, IET Radar, Sonar & Navigation, vol. 5, no. 2, pp. 182-193, February 2011.
  25. Coupled Non-Parametric Shape and Moment-Based Inter-Shape Pose Priors for Multiple Basal Ganglia Structure Segmentation,” Gokhan Uzunbas, Octavian Soldea, Devrim Unay, Müjdat Çetin, Gozde Unal, Aytül Erçil, and Ahmet Ekin, IEEE Trans. Medical Imaging, vol. 29, no. 12, pp. 1959-1978, December 2010.
  26. Sparsity and Compressed Sensing in Radar Imaging,” Lee Potter, Emre Ertin, Jason T. Parker, and Müjdat Çetin, Proceedings of the IEEE, vol. 98, no. 6, pp. 1006-1020, June 2010.
  27. Learning the Dynamics and Time-Recursive Boundary Detection of Deformable Objects,” Walter Sun, Müjdat Çetin, Raymond Chan, and Alan S. Willsky, IEEE Trans. Image Processing, vol. 17, no. 11, pp. 2186-2200, November 2008.
  28. Sparse Signal Representation in Structured Dictionaries with Application to Synthetic Aperture Radar,” Kush R. Varshney, Müjdat Çetin, John W. Fisher III, and Alan S. Willsky, IEEE Trans. Signal Processing, vol. 56, no. 8, pp. 3548-3561, August 2008.
  29. Nonparametric Shape Priors for Active Contour-based Image Segmentation,” Junmo Kim, Müjdat Çetin, and Alan S. Willsky, Signal Processing, vol. 87, no. 12, pp. 3021-3044, December 2007.
  30. Distributed Fusion in Sensor Networks: A Graphical Models Perspective,” Müjdat Çetin, Lei Chen, John W. Fisher III, Alexander T. Ihler, Randolph L. Moses, Martin J. Wainwright, and Alan S. Willsky, IEEE Signal Processing Magazine, vol. 23, no. 4, pp. 42-55, July 2006.
  31. Data Association based on Optimization in Graphical Models with Application to Sensor Networks,” Lei Chen, Martin Wainwright, Müjdat Çetin, and Alan S. Willsky, Mathematical and Computer Modelling, Special Issue on Optimization and Control for Military Applications, vol. 43, nos. 9-10, pp. 1114-1135, May 2006.
  32. Variational Approaches on Discontinuity Localization and Field Estimation in Sea Surface Temperature and Soil Moisture Interpolations,” Walter Sun, Müjdat Çetin, W. Carlisle Thacker, T. Mike Chin, and Alan S. Willsky, IEEE Trans. Geoscience and Remote Sensing, vol. 44, no. 2, pp. 336-350, February 2006.
  33. A Feature-Preserving Regularization Method for Complex-valued Inverse Problems with Application to Coherent Imaging,” Müjdat Çetin, W. Clem Karl, and Alan S. Willsky, Optical Engineering, vol. 54, no. 1, 017003, January 2006.
  34. A Nonparametric Statistical Method for Image Segmentation using Information Theory and Curve Evolution,” Junmo Kim, John W. Fisher III, Anthony Yezzi, Jr., Müjdat Çetin, and Alan S. Willsky, IEEE Trans. Image Processing, vol. 14, no. 10, pp. 1486-1502, October 2005.
  35. A Sparse Signal Reconstruction Perspective for Source Localization with Sensor Arrays,” Dmitry M. Malioutov, Müjdat Çetin, and Alan S. Willsky, IEEE Trans. Signal Processing, vol. 53, no. 8, pp. 3010-3022, August 2005.
  36. Region-Enhanced Passive Radar Imaging,” Müjdat Çetin and Aaron Lanterman, IEEE Proceedings Radar, Sonar & Navigation, Special Issue on Passive Radar Systems, vol. 152, no. 3, pp. 185-194, June 2005.
  37. Feature Enhancement and ATR Performance using Non-Quadratic Optimization-based SAR Imaging,” Müjdat Çetin, W. Clem Karl, and David A. Castañon, IEEE Trans. Aerospace and Electronic Systems, vol. 39, no. 4, pp. 1375-1395, October 2003.
  38. Feature-enhanced synthetic aperture radar image formation based on nonquadratic regularization,” Müjdat Çetin and W. Clem Karl, IEEE Trans. Image Processing, vol. 10, no. 4, pp. 623-631, April 2001.
  39. “Balancing and attitude control of double and triple inverted pendulums,” G. A. Medrano-Cerda, E. E. Eldukhri, and M. Çetin, Transactions of the Institute of Measurement and Control, vol. 17, no. 3, pp. 143-154, 1995.
    Book Chapters

  1. “Decentralized Human Tracking in Visual Sensor Networks: Using Sparse Representation for Efficient Communication,” Serhan Cosar and Müjdat Çetin, in Human Behaviour Understanding in Networked Sensing, P. Spagnolo, P. L. Mazzeo and C. Distante (eds.), Springer, pp. 45-73, 2014 (ISBN: 978-3-319-10806-3).
  2. “Sparsity and Compressed Sensing in Mono-static and Multi-static Radar Imaging,” Ivana Stojanovic, Müjdat Çetin, and W. Clem Karl, in Compressed Sensing and Sparse Filtering, A. Carmi, L. Mihaylova, and S. J. Godsill (eds.), Springer, pp. 395-421, 2014 (ISBN: 978-3642383984).
  3. “Machine Learning Systems for Detecting Driver Drowsiness,” Esra Vural, Müjdat Çetin, Aytül Erçil, Gwen Littlewort, Marian Bartlett, and Javier Movellan, in In-Vehicle Corpus and Signal Processing for Driver Behavior, K. Takeda, J.H.L. Hansen, H. Erdogan, and H. Abut (eds.), Springer, pp. 97-110, November 2008 (ISBN: 978-0387795812).
  4. “Datamining spontaneous facial behavior with automatic expression coding,” Marian Bartlett, Gwen Littlewort, Javier Movellan, Esra Vural, Kang Lee, Müjdat Çetin, and Aytül Erçil, in Verbal and Nonverbal Features of Human-Human and Human-Machine Interaction, 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).
  5. “Graphical Models and Fusion in Sensor Networks,” Müjdat Çetin, 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, A. Swami, Q. Zhao, Y.-W. Hong, and L. Tong (eds.), John Wiley and Sons, pp. 215-249, December 2007 (ISBN: 978-0470035573).
    Conference Papers

  1. Pre-Movement Contralateral EEG Low Beta Power is Modulated with Motor Adaptation Learning,” Ozan Özdenizci, Mustafa Yalçın, Ahmetcan Erdoğan, Volkan Patoğlu, Moritz Grosse-Wentrup, and Müjdat Çetin, IEEE International Conference on Acoustics, Speech, and Signal Processing, 2017.
  2. Disjunctive Normal Shape Boltzmann Machine,” Ertunç Erdil, Fitsum Mesadi, Tolga Taşdizen, and Müjdat Çetin, IEEE International Conference on Acoustics, Speech, and Signal Processing, 2017.
  3. Dendritic Spine Shape Analysis: A Clustering Perspective,” M. Usman Ghani, Ertunç Erdil, Sümeyra Demir Kanık, A. Ozgür Argunşah, Anna Felicity Hobbiss, Inbal Israely, Devrim Unay, Tolga Taşdizen, and Müjdat Çetin, European Conference on Computer Vision, BioImage Computing Workshop, 2016.

  4. Disjunctive Normal Level Set: An Efficient Parametric Implicit Method,” Fitsum Mesadi, Müjdat Çetin, and Tolga Taşdizen, IEEE International Conference on Image Processing, 2016.

  5. Context-Aware Hybrid Classification System for Fine-Grained Retail Product Recognition,” İpek Baz, Erdem Yörük, and Müjdat Çetin, IEEE Image, Video, and Multidimensional Signal Processing Workshop, 2016.

  6. MCMC Shape Sampling for Image Segmentation with Nonparametric Shape Priors,” Ertunç Erdil, Tolga Taşdizen, and Müjdat Çetin, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.

  7. Resting-State EEG Correlates of Motor Learning Performance in a Force-Field Adaptation Task,” Ozan Ozdenizci, Mustafa Yalçın, Ahmetcan Erdoğan, Volkan Patoğlu, Moritz Grosse-Wentrup, and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, International Workshop on Machine Learning for Understanding the Brain, 2016.

  8. Classification of Motor Task Execution Speed from EEG Data,” Sezen Yağmur Günay, Elif Hocaoğlu, Volkan Patoğlu, and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, International Workshop on Machine Learning for Understanding the Brain, 2016.

  9. Disjunctive Normal Unsupervised LDA for P300-based Brain-Computer Interfaces,” Majed Elwardy, Tolga Taşdizen, and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, International Workshop on Machine Learning for Understanding the Brain, 2016.

  10. Dendritic Spine Classification based on Two-Photon Microscopic Images using Sparse Representation,” M. Usman Ghani, Sümeyra Demir Kanık, A. Ozgür Argunşah, Inbal Israely, Devrim Ünay, and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, 2016 (in Turkish).

  11. Detection of Motor Task Difficulty Level from EEG Data,” Sezen Yağmur Günay, Elif Hocaoğlu, Volkan Patoğlu, and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, 2016 (in Turkish).

  12. Joint Nonparametric Shape and Feature Density Estimation for Segmentation of Dendritic Spines,” Ertunç Erdil, Lavdie Rada, A. Ozgür Argunşah, Inbal Israely, Devrim Ünay, Tolga Taşdizen, and Müjdat Çetin, IEEE International Symposium on Biomedical Imaging, 2016.

  13. Dendritic Spine Shape Analysis Using Disjunctive Normal Shape Models,” M. Usman Ghani, Fitsum Mesadi, Sümeyra Demir Kanık, A. Ozgür Argunşah, Inbal Israely, Devrim Unay, Tolga Taşdizen, and Müjdat Çetin, IEEE International Symposium on Biomedical Imaging, 2016.

  14. On Comparison of Manifold Learning Techniques for Dendritic Spine Classification,” M. Usman Ghani, A. Ozgür Argunşah, Inbal Israely, Devrim Ünay, Tolga Taşdizen, and Müjdat Çetin, IEEE International Symposium on Biomedical Imaging, 2016.

  15. Disjunctive Normal Shape and Appearance Priors with Applications to Image Segmentation,” Fitsum Mesadi, Müjdat Çetin, and Tolga Taşdizen, International Conference on Medical Image Computing and Computer Assisted Interventions, 2015.

  16. An Augmented Lagrangian Method for Image Reconstruction with Multiple Features,” H. Emre Güven, Alper Güngör, and Müjdat Çetin, IEEE International Conference on Image Processing, 2015.

  17. Design and Comparative Evaluation of a BCI-based Upper Extremity Robotic Rehabilitation Protocol,” Ela Koyaş, Mine Saraç, Müjdat Çetin, and Volkan Patoğlu, IEEE International Conference on Rehabilitation Robotics, 2015.

  18. An Augmented Lagrangian Method for Autofocused Compressed SAR Imaging,” Alper Güngör, Müjdat Çetin, and H. Emre Güven, International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, 2015.

  19. Low-rank Sparse Matrix Decomposition for Sparsity-driven SAR Image Reconstruction,” Abdurrahim Soğanlı and Müjdat Çetin, International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, 2015.

  20. Dendritic Spine Shape Classification from Two-Photon Microscopy Images,” Usman Ghani, Sumeyra Demir Kanık, A. Ozgür Argunşah, Tolga Taşdizen, Devrim Ünay, and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, 2015 (in Turkish).

  21. Adaptive Neurofeedback on Parieto-Occipital Cortex for Motor Learning Performance,” Ozan Ozdenizci, Timm Meyer, Müjdat Çetin, and Moritz Grosse-Wentrup, IEEE Conference on Signal Processing, Communications, and their Applications, 2015 (in Turkish).

  22. Sparsity-driven SAR Image Reconstruction via Low-rank Sparse Matrix Decomposition,” Abdurrahim Soğanlı and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, 2015 (in Turkish).

  23. Semi-supervised Adaptation of Motor Imagery Based BCI Systems,” Ismail Yılmaz, Sumeyra Demir Kanık, Tolga Taşdizen, and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, 2015 (in Turkish).

  24. Automated Dendritic Spine Tracking on 2-Photon Microscopic Images,” Bike Kılıç, Lavdie Rada, Ertunç Erdil, A. Ozgür Argunşah, Müjdat Çetin, and Devrim Ünay, IEEE Conference on Signal Processing, Communications, and their Applications, 2015 (in Turkish).

  25. Information-Theoretic Noisy Band Detection in Hyperspectral Imagery,” Mustafa Ergül, Fatih Nar, Emre Akyılmaz, Nigar Şen, and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, 2015 (in Turkish).

  26. Disjunctive Normal Shape Models,” Nisha Ramesh, Fitsum Mesadi, Müjdat Çetin, and Tolga Taşdizen, IEEE International Symposium on Biomedical Imaging, 2015.

  27. A Joint Classification and Segmentation Approach for Dendritic Spine Segmentation in 2-Photon Microscopy Images,” Ertunç Erdil, A. Ozgür Argunşah, Tolga Taşdizen, Devrim Ünay, and Müjdat Çetin, IEEE International Symposium on Biomedical Imaging, 2015.

  28. Dictionary Learning for Sparsity-driven SAR Image Reconstruction,” Abdurrahim Soğanlı and Müjdat Çetin, IEEE International Conference on Image Processing, 2014.

  29. Automatic Dendritic Spine Detection using Multiscale Dot Enhancement Filters and SIFT Features,” Lavdie Rada, Ertunç Erdil, A. Ozgür Argunşah, Devrim Ünay, and Müjdat Çetin, IEEE International Conference on Image Processing, 2014.

  30. Towards Neurofeedback Training of Associative Brain Areas for Stroke Rehabilitation,” Ozan Ozdenizci, Timm Meyer, Müjdat Çetin, and Moritz Grosse-Wentrup, International Brain-Computer Interface Conference, 2014.

  31. A Probabilistic Graphical Model for Word-Level Language Modeling in P300 Spellers,” Jaime Fernando Delgado Saa, Adriana de Pesters, Dennis McFarland, and Müjdat Çetin, International Brain-Computer Interface Conference, 2014.

  32. An Augmented Lagrangian Method for Sparse SAR Imaging,” H. Emre Guven and Müjdat Çetin, European Conference on Synthetic Aperture Radar, 2014 (Invited Paper).

  33. An Accelerated Augmented Lagrangian Method with application to Compressed Sensing SAR Imaging,” Ertunç Erdil, A. Ozgür Argunşah, Devrim Ünay, and Müjdat Çetin, National Neuroscience Congress, 2014 (in Turkish).

  34. An Accelerated Augmented Lagrangian Method with application to Compressed Sensing SAR Imaging,” H. Emre Güven and Müjdat Çetin, NATO SET-213 Specialist Meeting on Compressive Sensing for Radar/SAR and EO/IR Imaging, 2014.

  35. Dictionary Learning-based Approach for SAR Image Reconstruction,” Abdurrahim Soğanlı and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Trabzon, Turkey, April 2014 (in Turkish).

  36. Detection of Task Difficulty From Intention Level Information in the EEG Features,” Ela Koyaş, Elif Hocaoğlu, Müjdat Çetin, and Volkan Patoğlu, IEEE Conference on Signal Processing, Communications, and their Applications, Trabzon, Turkey, April 2014 (in Turkish).

  37. An Alternating Direction Method of Multipliers for Sparse SAR Imaging,” H. Emre Güven and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Trabzon, Turkey, April 2014 (in Turkish).

  38. A Robust Nonlinear Scale Space Change Detection Approach for SAR Images,” Berk Sevilmiş, O. Erman Okman, Fatih Nar, Can Demirkesen, and Müjdat Çetin, SPIE Remote Sensing Symposium, 2013.

  39. Detection of Intention Level in Response to Task Difficulty from EEG Signals,” Ela Koyaş, Elif Hocaoğlu, Volkan Patoğlu, and Müjdat Çetin, IEEE International Workshop on Machine Learning for Signal Processing, 2013 (Invited paper).

  40. SAR Moving Target Imaging Using Group Sparsity,” Ozben Onhon and Müjdat Çetin, EURASIP European Signal Processing Conference, 2013.

  41. A Sparsity-Driven Approach to Multi-camera Tracking in Visual Sensor Networks,” Serhan Coşar and Müjdat Çetin, IEEE International Conference on Advanced Video and Signal-based Surveillance, Workshop on Activity Monitoring by Multiple Distributed Sensing, 2013.

  42. Incorporation of a Language Model into a Brain Computer Interface based Speller through HMMs,” Çağdaş Ulaş and Müjdat Çetin, IEEE International Conference on Acoustics, Speech, and Signal Processing, 2013.

  43. Brain Computer Interface based Robotic Rehabilitation with Online Modification of Task Speed,” Mine Saraç, Ela Koyaş, Ahmetcan Erdoğan, Volkan Patoğlu, and Müjdat Çetin, International Conference on Rehabilitation Robotics, 2013.

  44. The First Brain-Computer Interface Utilizing a Turkish Language Model,” Çağdaş Ulaş and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Girne, North Cyprus, April 2013 (in Turkish).

  45. Control of a BCI-based Upper Limb Rehabilitation System Utilizing Posterior Probabilities,” Ela Koyaş, Mine Saraç, Ahmetcan Erdoğan, Müjdat Çetin, and Volkan Patoğlu, IEEE Conference on Signal Processing, Communications, and their Applications, Girne, North Cyprus, April 2013 (in Turkish).

  46. A Watershed and Active Contours Based Method for Dendritic Spine Segmentation in 2-Photon Microscopy Images,” Ertunç Erdil, A. Özgür Argunşah, Devrim Ünay, and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Girne, North Cyprus, April 2013 (in Turkish).

  47. Biomedical Image Time Series Registration with Particle Filtering,” A. Murat Yağcı Ertunç Erdil, A. Özgür Argunşah, Devrim Ünay, Müjdat Çetin, Lale Akarun, and Fikret Gürgen, IEEE Conference on Signal Processing, Communications, and their Applications, Girne, North Cyprus, April 2013 (in Turkish).

  48. Interactive Ship Segmentation in SAR Images,” Emre Akyılmaz, Can Demirkesen, Fatih Nar, O. Erman Okman, and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Girne, North Cyprus, April 2013 (in Turkish).

  49. Automatic and Semi-automatic Extraction of Curvilinear Features from SAR Images,” Emre Akyilmaz, O. Erman Okman, Fatih Nar, and Müjdat Çetin, SPIE Security + Defence Symposium, SAR Image Analysis, Modeling, and Techniques Conference, Edinburgh, United Kingdom, September 2012.
  50. Region Based Target Detection in Synthetic Aperture Radar Images and its Parallel Implementation,” Can Demirkesen, O. Erman Okman, Fatih Nar, and Müjdat Çetin, Sixth Defense Technologies Conference, Ankara, Turkey, June 2012 (in Turkish).
  51. Segmentation of Inhomogeneous Foreground and Background Intensity Objects Using a Probability Density Function Based Data Term and Nonparametric Shape Priors,” Abdurrahim Soganli and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Mugla, Turkey, April 2012 (in Turkish).
  52. Region Based Target Detection Approach for Synthetic Aperture Radar Images and its Parallel Implementation,” Fatih Nar, Can Demirkesen, O. Erman Okman, and Müjdat Çetin, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XIX, E. G. Zelnio and F. D. Garber, Eds., Baltimore, Maryland, USA, April 2012.
  53. Handling Phase in Sparse Reconstruction for SAR: Imaging, Autofocusing, and Moving Targets,” Müjdat Çetin, Ozben Onhon, and Sadegh Samadi, European Conference on Synthetic Aperture Radar, Nuremberg, Germany, April 2012.
  54. Feature Preserving SAR Despeckling and its Parallel Implementation with Application to Railway Detection,” O. Erman Okman, Fatih Nar, Can Demirkesen, and Müjdat Çetin, European Conference on Synthetic Aperture Radar, Nuremberg, Germany, April 2012.
  55. A Group Sparsity-Driven Approach to 3-D Action Recognition,” Serhan Cosar and Müjdat Çetin, IEEE International Conference on Computer Vision, Workshop on Visual Surveillance, Barcelona, Spain, November 2011.
  56. Sparsity-driven Image Formation and Space-variant Focusing for SAR,” Ozben Onhon and Müjdat Çetin, IEEE International Conference on Image Processing, Brussels, Belgium, September 2011.
  57. Hidden Conditional Random Fields for Classification of Imaginary Motor Tasks From EEG Data,” Jaime Fernando Delgado Saa and Müjdat Çetin, EURASIP European Signal Processing Conference,
    Barcelona, Spain, August 2011.
  58. SAR Moving Target Imaging in a Sparsity-driven Framework,” Ozben Onhon and Müjdat Çetin, SPIE Optics + Photonics Symposium, Wavelets and Sparsity XIV Conference, San Diego, California, USA, August 2011.
  59. A Region-based Target Detection Method for SAR Images,” Fatih Nar, Can Demirkesen, O. Erman Okman, and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Antalya, Turkey, April 2011 (in Turkish).
  60. Sparsity-driven Spatio-temporal EEG Source Estimation,” Ozge Batu and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Antalya, Turkey, April 2011 (in Turkish).
  61. A Sparsity-driven Approach for SAR Image Formation and Space-variant Focusing,” Ozben Onhon and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Antalya, Turkey, April 2011 (in Turkish).
  62. AR-PCA-HMM Approach for Sensorimotor Task Classification in EEG-based Brain-Computer Interfaces,” Ali Ozgur Argunsah and Müjdat Çetin, International Conference on Pattern Recognition, Istanbul, Turkey, August 2010.
  63. Design, Implementation and Evaluation of a Real-time P300-based Brain-Computer Interface System,” Armagan Amcalar and Müjdat Çetin, International Conference on Pattern Recognition, Istanbul, Turkey, August 2010.
  64. Discrimination of Moderate and Acute Drowsiness Based on Spontaneous Facial Expressions,” Esra Vural, Marian Bartlett, Gwen Littlewort, Müjdat Çetin, Aytül Erçil, and Javier Movellan, International Conference on Pattern Recognition, Istanbul, Turkey, August 2010.
  65. Segmentation of Anatomical Structures in Brain MR Images Using Atlases in FSL – A Quantitative Approach,” Octavian Soldea, Ahmet Ekin, Diana F. Soldea, Devrim Unay, Müjdat Çetin, Aytül Erçil, Gokhan Uzunbas, Zeynep Firat, and Mutlu Cihangiroglu, International Conference on Pattern Recognition, Istanbul, Turkey, August 2010.
  66. Sparsity-driven Focused SAR Image Formation,” Ozben Onhon and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Diyarbakir, Turkey, April 2010 (in Turkish).
  67. A Brain-Computer Interface Algorithm based on Hidden Markov Models and Dimensionality Reduction,” Ali Ozgur Argunsah and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Diyarbakir, Turkey, April 2010 (in Turkish).
  68. A Brain-Computer Interface System for Online Spelling,” Armagan Amcalar and Müjdat Çetin, IEEE Conference on Signal
    Processing, Communications, and their Applications,
    Diyarbakir, Turkey, April 2010 (in Turkish).
  69. Joint Sparsity-Driven Inversion and Model Error Correction for Radar Imaging,” Ozben Onhon and Müjdat Çetin, IEEE International Conference on Acoustics, Speech, and Signal Processing, Dallas, Texas, USA, March 2010.
  70. Automated X-Ray Image Annotation: Single versus Ensemble of Support Vector Machines,” Devrim Unay, Octavian Soldea, Sureyya Ozogur-Akyuz, Müjdat Çetin, and Aytül Erçil, European Conference on Digital Libraries (ECDL), Cross-Language Evaluation Forum (CLEF) Workshop, Corfu, Greece, September-October 2009.
  71. Detection of Eye Blinks from EEG using Hidden Markov Models,” Ali Ozgur Argunsah, Baran Curuklu, and Müjdat Çetin, Swedish Association of Medical Engineering and Physics, Medical Technology Days,, Vasteras, Sweden, September 2009.
  72. Analysis of EEG Signals for Brain Computer Interface,” Jessy Parokaran, Ali Ozgur Argunsah, Baran Curuklu, and Müjdat Çetin, Swedish Association of Medical Engineering and Physics, Medical Technology Days,, Vasteras, Sweden, September 2009.
  73. Automatic Annotation of X-ray Images: A Study on Attribute Selection, Devrim Unay, Octavian Soldea, Ahmet Ekin, Müjdat Çetin, and Aytül Erçil, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Workshop on Medical Content-based Retrieval for Clinical Decision Support, London, UK, September 2009.
  74. An Efficient Monte Carlo Approach for Optimizing Decentralized Estimation Networks Constrained by Undirected Topologies,” Murat Uney and Müjdat Çetin, IEEE Workshop on Statistical Signal Processing, Cardiff, Wales, August-September 2009.
  75. An Efficient Monte Carlo Approach for Optimizing Communication-Constrained Decentralized Estimation Networks,” Murat Uney and Müjdat Çetin, EURASIP European Signal Processing Conference, Glasgow, Scotland, August 2009.
  76. An Efficient Message Passing Algorithm for Multi-Target Tracking,” Zhexu (Michael) Chen, Lei Chen, Müjdat Çetin, and Alan
    S. Willsky, International Conference on Information Fusion, Seattle, Washington, USA, July 2009.
  77. Volumetric Segmentation of Multiple Basal Ganglia Structures using Nonparametric Coupled Shape and Inter-Shape Pose Priors,” Gokhan Uzunbas, Octavian Soldea, Müjdat Çetin, Gozde Unal, Aytül Erçil, Devrim Unay, Ahmet Ekin, and Zeynep Firat IEEE International Symposium on Biomedical Imaging, Boston, Massachusetts, USA, June 2009.
  78. Volumetric Segmentation of Multiple Basal Ganglia Structures,” Gokhan Uzunbas, Octavian Soldea, Müjdat Çetin, Gozde Unal, and Aytül Erçil, and Ahmet Ekin, Israeli Symposium on Computer-Aided Surgery, Medical Robotics, and Medical Imaging, Tel Aviv, Israel, May 2009.
  79. A Nonquadratic Regularization-based Technique for Joint SAR Imaging and Model Error Correction,” Ozben Onhon and Müjdat Çetin, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XVI, E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, April 2009.
  80. Compressed sensing of mono-static and multi-static SAR,” Ivana Stojanovic, W. Clem Karl, and Müjdat Çetin, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XVI, E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, April 2009.
  81. Multiple Feature-Enhanced Synthetic Aperture Radar Imaging,” Sadegh Samadi, Müjdat Çetin, and Mohammad Ali Masnadi-Shirazi,
    SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XVI, E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, April 2009.
  82. Decentralized Random-Field Estimation Under Communication Constraints,” Murat Uney and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Antalya, Turkey, April 2009 (in Turkish).
  83. A Nonquadratic Regularization Based Image Reconstruction Technique for SAR Data with Phase Errors,” Ozben Onhon and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Antalya, Turkey, April 2009 (in Turkish).
  84. Multi-Object Segmentation using Coupled Nonparametric Shape and Relative Pose Priors,” Gokhan Uzunbas, Octavian Soldea, Müjdat Çetin, Gozde Unal, and Aytül Erçil, Devrim Unay, Ahmet Ekin, and Zeynep Firat IS&T/SPIE Electronic Imaging, Computational Imaging VII, San Jose, California, USA, January 2009.
  85. Binary and nonbinary description of hypointensity for search and retrieval of brain MR images, Devrim Unay, Xiaojing Chen, Aytül Erçil, Müjdat Çetin, Radu Jasinschi, Mark A. van Buchem, and Ahmet Ekin, IS&T/SPIE Electronic Imaging, Multimedia Content Access: Algorithms and Systems III, San Jose, California, USA, January 2009.
  86. Sparse Signal Representation for Complex-valued Imaging,” Sadegh Samadi, Müjdat Çetin, and Mohammad Ali Masnadi-Shirazi, IEEE Signal Processing Society 13th DSP Workshop & 5th SPE Workshop, Marco Island, Florida, USA, January 2009.
  87. “Automated Drowsiness Detection For Improved Driving Safety,” Esra Vural, Müjdat Çetin, Aytül Erçil, Gwen Littlewort, Marian Bartlett, and Javier Movellan, International Conference on Automotive Technologies, Istanbul, Turkey, November 2008.
  88. Segmentation of the Evolving Left Ventricle by Learning the Dynamics,” Walter Sun, Müjdat Çetin, Ray Chan, and Alan S. Willsky, IEEE International Symposium on Biomedical Imaging, Paris, France, May 2008.
  89. Coupled Nonparametric Shape Priors for Segmentation of Multiple Basal Ganglia Structures,” Gokhan Uzunbas, Müjdat Çetin, Gozde Unal, and Aytül Erçil, IEEE International Symposium on Biomedical Imaging, Paris, France, May 2008.
  90. Hyper-parameter Selection in Advanced Synthetic Aperture Radar Imaging Algorithms,” Ozge Batu and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Aydin, Turkey, April 2008 (in Turkish).
  91. Target Localization in Acoustic Sensor Networks Using Factor Graphs,” Murat Uney and Müjdat Çetin, IEEE Conference on Signal Processing, Communications, and their Applications, Aydin, Turkey, April 2008 (in Turkish).
  92. Detecting Driver Drowsiness Using Computer Vision Techniques,” Esra Vural, Müjdat Çetin, Aytül Erçil, Gwen Littlewort, Marian Bartlett, and Javier Movellan, IEEE Conference on Signal Processing, Communications, and their Applications, Aydin, Turkey, April 2008 (in Turkish).
  93. Stereo-based 3D Head Pose Tracking using the Scale Invariant Feature Transform,” Batu Akan, Müjdat Çetin, and Aytül Erçil, IEEE Conference on Signal Processing, Communications, and their Applications, Aydin, Turkey, April 2008 (in Turkish).
  94. Segmentation of Multiple Brain Structures Using Coupled Nonparametric Shape Priors,” Gokhan Uzunbas, Müjdat Çetin, Gozde Unal, and Aytül Erçil, IEEE Conference on Signal Processing, Communications, and their Applications, Aydin, Turkey, April 2008 (in Turkish).
  95. Joint space aspect reconstruction of wide-angle SAR exploiting sparsity,” Ivana Stojanovic, Müjdat Çetin, and W. Clem Karl, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XV, E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, March 2008.
  96. Hyper-parameter Selection in Non-quadratic Regularization-based Radar Image Formation,” Ozge Batu and Müjdat Çetin, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XV, E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, March 2008.
  97. Drowsy Driver Detection Through Facial Movement Analysis,” Esra Vural, Müjdat Çetin, Aytül Erçil, Gwen Littlewort, Marian Bartlett, and Javier Movellan, IEEE International Conference on Computer Vision, Human Computer Interaction Workshop, Rio de Janeiro, Brazil, October 2007.
  98. Graphical Model-based Approaches to Target Tracking in Sensor Networks: An Overview of Some Recent Work and Challenges,” Murat Uney and Müjdat Çetin, IEEE International Symposium on Image and Signal Processing and Analysis, Istanbul, Turkey, September 2007.
  99. A Robust Facial Feature Point Tracker using Graphical Models,” Serhan Cosar, Müjdat Çetin, and Aytül Erçil, IEEE International Symposium on Image and Signal Processing and Analysis, Istanbul, Turkey, September 2007.
  100. Shape and Data-Driven Texture Segmentation using Local Binary Patterns,” Erkin Tekeli, Müjdat Çetin, and Aytül Erçil, EURASIP European Signal Processing Conference, Poznan, Poland, September 2007.
  101. Robustness of Local Binary Patterns in Brain MR Image Analysis, Devrim Unay, Ahmet Ekin, Müjdat Çetin, Radu Jasinschi, and Aytül Erçil, International Conference of the IEEE Engineering in Medicine and Biology Society, Lyon, France, August 2007.
  102. Graphical Model based Facial Feature Point Tracking in a Vehicle Environment,” Serhan Cosar, Müjdat Çetin, and Aytül Erçil, Biennial on DSP for in-Vehicle and Mobile Systems, Istanbul, Turkey, June 2007.
  103. Machine Learning Systems for Detecting Driver Drowsiness,” Esra Vural, Müjdat Çetin, Aytül Erçil, Gwen Littlewort, Marian Bartlett, and Javier Movellan, Biennial on DSP for in-Vehicle and Mobile Systems, Istanbul, Turkey, June 2007.
  104. 3D Head Tracking using Normal Flow Constraints in a Vehicle Environment,” Batu Akan, Müjdat Çetin, and Aytül Erçil, Biennial on DSP for in-Vehicle and Mobile Systems, Istanbul, Turkey, June 2007.
  105. A Sparse Signal Representation-based Approach to Image Formation and Anisotropy Determination in Wide-Angle Radar,” Kush R. Varshney, Müjdat Çetin, John W. Fisher III, and Alan S. Willsky, IEEE Conference on Signal Processing and Communications Applications, Eskisehir, Turkey, June 2007 (in Turkish).
  106. Non-quadratic Regularization Based Image Deblurring: Automatic Parameter Selection and Feature Based Evaluation),” Ozge Batu and Müjdat Çetin, IEEE Conference on Signal Processing and Communications Applications, Eskisehir, Turkey, June 2007 (in Turkish).
  107. Eye Feature Point Tracking by Using Graphical Models,” Serhan Cosar and Müjdat Çetin, IEEE Conference on Signal Processing and Communications Applications, Eskisehir, Turkey, June 2007 (in Turkish).
  108. Factors that Affect Classification Performance in EEG based Brain-Computer Interfaces,” Ali Ozgur Argunsah, Ali Baran Curuklu, Müjdat Çetin, and Aytül Erçil, IEEE Conference on Signal Processing and Communications Applications, Eskisehir, Turkey, June 2007 (in Turkish).
  109. A Local Binary Patterns and Shape Priors based Texture Segmentation Method),” Erkin Tekeli, Müjdat Çetin, and Aytül Erçil, IEEE Conference on Signal Processing and Communications Applications , Eskisehir, Turkey, June 2007 (in Turkish).
  110. A Novel Feature Extraction Method for Improving P300-Speller Performance,” Ali Ozgur Argunsah, Ali Baran Curuklu, Müjdat Çetin, and Aytül Erçil, Applied Neuroscience for Healthy Brain Function Scientific Meeting, Nijmegen, The Netherlands, May 2007.
  111. “Machine Learning Systems for Detecting Driver Drowsiness,” Esra Vural, Müjdat Çetin, Aytül Erçil, Marian Bartlett, and Javier Movellan, Workshop for Women in Machine Learning, San Diego, California, USA, October 2006.
  112. Wide-Angle SAR Image Formation with Migratory Scattering Centers and Regularization in Hough Space,” Kush R. Varshney, Müjdat Çetin, John W. Fisher III, and Alan S. Willsky, Adaptive Sensor Array Processing Workshop, Lexington, Massachusetts, June 2006.
  113. Sparsity-Driven Sparse-Aperture Ultrasound Imaging,” Müjdat Çetin, Emmanuel Bossy, Robin Cleveland, and W. Clem Karl, IEEE International Conference on Acoustics, Speech, and Signal Processing, Toulouse, France, May 2006.
  114. Joint Image Formation and Anisotropy Characterization in Wide-Angle SAR,” Kush R. Varshney, Müjdat Çetin, John W. Fisher III, and Alan S. Willsky, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XIII, E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, April 2006.
  115. Synthetic Aperture Radar Imaging from Wide-Angle Data with Frequency-Band Omissions,” Müjdat Çetin and Randolph L. Moses, IEEE Conference on Signal Processing and Communications Applications, Antalya, Turkey, April 2006 (in Turkish).
  116. Intrinsic Image Estimation and Image Deblurring for Microscopic Images,” Eray Dogan and Müjdat Çetin, IEEE Conference on Signal Processing and Communications Applications, Antalya, Turkey, April 2006 (in Turkish).
  117. A Fast Algorithm for Vision-based Hand Gesture Recognition for Robot Control ,” Asanterabi Malima, Erol Ozgur, and Müjdat Çetin, IEEE Conference on Signal Processing and Communications Applications, Antalya, Turkey, April 2006.
  118. Nonparametric Shape Priors for Active Contour-based Image Segmentation,” Junmo Kim, Müjdat Çetin, and Alan S. Willsky, EURASIP European Signal Processing Conference (EUSIPCO), Antalya, Turkey, September 2005.
  119. Distributed Data Association for Multi-Target Tracking in Sensor Networks,” Lei Chen, Müjdat Çetin, and Alan S. Willsky, International Conference on Information Fusion, Philadelphia, Pennsylvania, July 2005. (Best Student Paper Award)
  120. Segmenting and Tracking the Left Ventricle by Learning the Dynamics in Cardiac Images,” Walter Sun, Müjdat Çetin, Ray Chan, Vivek Reddy, Fred Holmvang, Venkat Chandar, and Alan S. Willsky, Information Processing in Medical Imaging, Glenwood Springs, Colorado, July 2005.
  121. “Graphical Model-Based Algorithms for Data Association in Distributed Sensing,” Lei Chen, Müjdat Çetin, and Alan S. Willsky, Adaptive Sensor Array Processing Workshop, Lexington, Massachusetts, June 2005.
  122. Collaborative Distributed Inference with Minimal Online Communication,” O. Patrick Kreidl, Müjdat Çetin, and Alan S. Willsky, The Learning Workshop, Snowbird, Utah, April 2005.
  123. SAR imaging from partial-aperture data with frequency-band omissions,” Müjdat Çetin and Randy L. Moses, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XII, E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, March-April 2005.
  124. Homotopy Continuation for Sparse Signal Representation,” Dmitry M. Malioutov, Müjdat Çetin, and Alan S. Willsky, IEEE International Conference on Acoustics, Speech, and Signal Processing, Philadelphia, Pennsylvania, March 2005.
  125. Semi-Blind Sparse Channel Estimation with Constant Modulus Symbols,” Müjdat Çetin and Brian M. Sadler, IEEE International Conference on Acoustics, Speech, and Signal Processing, Philadelphia, Pennsylvania, March 2005.
  126. A Fast Hybrid Approach for SAR Classification,” Brian Huether, Timo Kempf, and Müjdat Çetin, European Conference on Synthetic Aperture Radar, Ulm, Germany, May 2004.
  127. Optimal Sparse Representations in General Overcomplete Bases,” Dmitry M. Malioutov, Müjdat Çetin, and Alan S. Willsky, IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 2, pp. 793-796, Montreal, Canada, May 2004.
  128. Region-Enhanced Imaging for Sparse-Aperture Passive Radar,” Müjdat Çetin and Aaron Lanterman, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XI, E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, April 2004.
  129. Wide Angle SAR Imaging,” Randy L. Moses, Lee Potter, and Müjdat Çetin, SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XI, E. G. Zelnio and F. D. Garber, Eds., Orlando, Florida, April 2004.
  130. Localization of Oceanic Fronts and Feature Boundaries Using a Variational Technique,” Walter Sun, Müjdat Çetin, W. Carlisle Thacker, T. Mike Chin, and Alan S. Willsky, American Geophysical Union Fall Meeting, San Francisco, California, December 2003. (Outstanding Student Paper Award)
  131. Data Fusion in Large Arrays of Microsensors,” Alan S. Willsky, Dmitry M. Malioutov, and Müjdat Çetin, Military Sensing Symposia (MSS) Specialty Group on Battlefield Acoustic and Seismic Sensing, Magnetic and Electric Field Sensors Symposium, October 2003.
  132. Source localization by enforcing sparsity through a Laplacian prior: an SVD-based approach,” Dmitry M. Malioutov, Müjdat Çetin, and Alan S. Willsky, IEEE Statistical Signal Processing Workshop, pp. 553-556, St. Louis, Missouri, September-October 2003.
  133. Incorporating Complex Statistical Information in Active Contour-based Image Segmentation,” Junmo Kim, John W. Fisher III, Müjdat Çetin, Anthony Yezzi, Jr., and Alan S. Willsky, IEEE International Conference on Image Processing, September 2003.
  134. A Unified Variational Approach to Denoising and Bias Correction in MR,” Ayres Fan, William Wells, John Fisher, Müjdat Çetin, Steven Haker, Robert Mulkern, Clare Tempany, and Alan S. Willsky, Information Processing in Medical Imaging, July 2003.
  135. An Edge-Preserving Regularization Method for Coherent Imaging Applications,” Müjdat Çetin, W. Clem Karl, and Alan S. Willsky, IEEE Conference on Signal Processing and Communications Applications, Istanbul, Turkey, June 2003 (in Turkish).
  136. Multitarget-Multisensor Data Association Using the Tree-Reweighted Max-Product Algorithm,” Lei Chen, Martin Wainwright, Müjdat Çetin, and Alan S. Willsky, SPIE AeroSense Symposium, Signal Processing, Sensor Fusion, and Target Recognition XII, I. Kadar, Ed., Proc. SPIE, vol. 5096, pp. 127-138, Orlando, Florida, April 2003.
  137. Application of Point Enhancement Technique for Ship Target Recognition by HRR,” Nilüfen Çotuk, Sedat Türe, and Müjdat Çetin, SPIE AeroSense Symposium, Algorithms for Synthetic Aperture Radar Imagery X, E. G. Zelnio and F. D. Garber, Eds., Proc. SPIE, vol. 5095, pp. 185-193, Orlando, Florida, April 2003.
  138. Edge-Preserving Image Reconstruction for Coherent Imaging Applications,” Müjdat Çetin, W. Clem Karl, and Alan S. Willsky, IEEE International Conference on Image Processing, vol. 2, pp. 481-484, Rochester, New York,
    September 2002.
  139. A Curve Evolution-Based Variational Approach to Simultaneous Image Restoration and Segmentation,” Junmo Kim, Andy Tsai, Müjdat Çetin, and Alan S. Willsky, IEEE International Conference on Image Processing, vol. 1, pp. 109-112, Rochester, New York, September 2002.
  140. Nonparametric Methods for Image Segmentation using Information Theory and Curve Evolution,” Junmo Kim, John W. Fisher III, Anthony Yezzi, Jr., Müjdat Çetin, and Alan S. Willsky, IEEE International Conference on Image Processing, vol. 3, pp. 797-800, Rochester, New York, September 2002.
  141. Super-resolution source localization through data-adaptive regularization,” Dmitry M. Malioutov, Müjdat Çetin, John W. Fisher III, and Alan S. Willsky, IEEE Sensor Array and Multichannel Signal Processing Workshop, pp. 194-198, Rosslyn, Virginia, August 2002.
  142. A Variational Technique for Source Localization based on a Sparse Signal Reconstruction Perspective,” Müjdat Çetin, Dmitry M. Malioutov, and Alan S. Willsky, IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 3, pp. 2965-2968, Orlando, Florida, May 2002.
  143. Analysis of the Impact of Feature-Enhanced SAR Imaging on ATR Performance,” Müjdat Çetin, W. Clem Karl, and David A. Castañon, SPIE AeroSense Symposium, Algorithms for Synthetic Aperture Radar Imagery IX, E.G. Zelnio, Ed., Proc. SPIE, vol. 4727, pp. 134-145, Orlando, Florida, April 2002.
  144. Formation of HRR Profiles by Non-Quadratic Optimization for Improved Feature Extraction,” Müjdat Çetin, W. Clem Karl, and David A. Castañon, SPIE AeroSense Symposium, Algorithms for Synthetic Aperture Radar Imagery IX, E.G. Zelnio, Ed., Proc. SPIE, vol. 4727, pp. 213-224, Orlando, Florida, April 2002.
  145. “Super-resolution source localization through data-adaptive regularization,” Dmitry M. Malioutov, Müjdat Çetin, John W. Fisher III, and Alan S. Willsky, Adaptive Sensor Array Processing Workshop, Lexington, Massachusetts, March 2002.
  146. “Complex-valued image reconstruction by half-quadratic regularization,” Müjdat Çetin and W. Clem Karl, SIAM Conference on Imaging Science, Boston, Massachusetts, March 2002.
  147. Superresolution and edge-preserving reconstruction of complex-valued synthetic aperture radar images,” Müjdat Çetin and W. Clem Karl, IEEE International Conference on Image Processing, vol. 1, pp. 701-704, Vancouver, Canada, September 2000.
  148. Enhanced, high resolution radar imaging based on robust regularization,” Müjdat Çetin and W. Clem Karl, IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 4, pp. 2278-2281, Istanbul, Turkey, June 2000.
  149. Evaluation of a regularized SAR imaging technique based on recognition-oriented features,” Müjdat Çetin, W. Clem Karl, and David A. Castañon, SPIE AeroSense Symposium, Algorithms for Synthetic Aperture Radar Imagery VII, E.G. Zelnio, Ed., Proc. SPIE, vol. 4053, pp. 40-51, Orlando, Florida, April 2000.
  150. Sentetik aciklikli radar ile goruntu gericatilmasina istatistiksel bir yaklasim,” Müjdat Çetin and W. Clem Karl, IEEE Conference on Signal Processing and its Applications, Ankara, Turkey, June 1999 (in Turkish).
  151. A statistical method for discrimination of natural terrain types from SAR data,” Müjdat Çetin and W. Clem Karl, IEEE International Conference on Image Processing, vol. 1, pp. 587-591, Chicago, Illinois, October 1998.
  152. A statistical tomographic approach to synthetic aperture radar image reconstruction,” Müjdat Çetin and W. Clem Karl, IEEE International Conference on Image Processing, vol. 1, pp. 845-848, Santa Barbara, California, October 1997.
  153. “Inversion and inference based on tomographic data,” Müjdat Çetin and W. Clem Karl, Progress in Electromagnetics Research Symposium, p. 573, Cambridge, Massachusetts, July 1997.
    Ph.D. Thesis
    Feature-Enhanced Synthetic Aperture Radar Imaging, Ph.D. thesis, Boston University, February 2001.