2019

  1. V. A. Sindagi and V. M. Patel, “HA-CCN: Hierarchical attention-based crowd counting network,” IEEE Transactions on Image Processing, accepted for publication, May 2019.
  2. H. Zhang, V. A. Sindagi and V. M. Patel, “Image de-raining using a conditional generative adversarial network,” IEEE Transactions on Circuits and Systems for Video Technology, accepted for publication, May 2019.
  3. P. Perera and V. M. Patel, “Learning deep features for one-class classification,” IEEE Transactions on Image Processing, accepted for publication, May 2019.
  4. H. Zhang, V. A. Sindagi and V. M. Patel, “Joint transmission map estimation and dehazing using deep networks,” IEEE Transactions on Circuits and Systems for Video Technology, accepted for publication, April 2019.
  5. M. Abavisani and V. M. Patel, “Deep sparse representation-based classification,” IEEE Signal Processing Letters, vol. 26, no. 6, pp. 948-952, June 2019.
  6. A. Z. Alsinan, V. M. Patel, and I. Hacihaliloglu, “Automatic segmentation of bone surfaces from ultrasound using a filter layer guided CNN,” International Journal of Computer Assisted Radiology and Surgery, vol. 14, no. 5, pp. 775-783, May 2019.
  7. E. Gonzalez-Sosa, R. Vera-Rodriguez, J. Fierrez, F. Alonso-Fernandez, and V. M. Patel, “Exploring body texture from mmW images for person recognition,” IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 1, no.2, pp. 139-151, Apr. 2019.
  8. H. Zhang, B. S. Riggan, S. Hu, N. J. Short, and V. M. Patel, “Synthesis of high-quality visible faces from polarimetric thermal faces using generative adversarial networks,” International Journal of Computer Vision: Special Issue on Deep Learning for Face Analysis, accepted for publication, Jan. 2019.
    (pdf)
  9. P. Oza and V. M. Patel, “One-class convolutional neural network,” IEEE Signal Processing Letters, vol. 26, no.2, pp. 277-281, Feb. 2019.(pdf)
  10. P. Perera and V. M. Patel, “Face-based multiple user active authentication on mobile devices,” IEEE Transactions on Information Forensics and Security, vol. 14, no.5, pp. 1240-1250, May 2019. (pdf)
  11. S. Wang, V. M. Patel and A. Petropulu, “Multidimensional sparse Fourier transform based on the Fourier projection-slice theorem,” IEEE Transactions on Signal Processing, vol. 67, no. 1, pp. 54-69, Jan. 2019. (pdf)
  12. R. Ranjan, V. M. Patel, and R. Chellappa, “HyperFace: a deep multi-task learning framework for face detection, landmark localization, pose estimation, and gender recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 1, pp. 121-135, Jan. 2019. (pdf)

2018

  1. M. Abavisani and V. M. Patel, “Deep multimodal subspace clustering networks,” IEEE Journal of Selected Topics in Signal Processing: Special issue on Data Science: Robust Subspace Learning and Tracking: Theory, Algorithms, and Applications, vol. 10, no.6, pp. 1601-1614, Dec. 2018. (pdf)
  2. H. Zhang and V. M. Patel, “Convolutional sparse and low-rank coding-based image decomposition”, IEEE Transactions on Image Processing, vol. 27, no. 5, pp. 2121 – 2133, May 2018.(pdf)
  3. R. Ranjan, S. Sankaranarayanan, A. Bansal, N. Bodla, J-C. Chen, V. M. Patel, C. D. Castillo and R. Chellappa, “Deep learning for understanding faces: machines may be just as good, or better, than humans”, IEEE Signal Processing Magazine: Special Issue on Deep Learning for Visual Understanding, vol. 35, no.1, pp. 66-83, Jan. 2018. (pdf)
  4. P. Perera and V. M. Patel, “Efficient and low latency detection of intruders in mobile active authentication”, IEEE Transactions on Information Forensics and Security, vol. 13, no. 6, pp. 1392-1405, June 2018. (pdf)
  5. V. A. Sindagi and V. M. Patel, “A survey of recent advances in CNN-based single image crowd counting and density estimation”,Pattern Recognition Letters, vol. 107, pp. 3-16, May 2018. (pdf)
  6.  C-H. Chen, V. M. Patel and R. Chellappa, “Learning from ambiguously labeled face images”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 7, pp. 1653-1667, July 2018. (pdf)
  7. J-C. Chen, R. Ranjan, S. Sankaranarayanan, A. Kumar, C-H. Chen, V. M. Patel, C. D. Castillo, and R. Chellappa, “Unconstrained still/video-based face verification with deep convolutional neural networks”, International Journal of Computer Vision, vol. 126, no. 2-4, pp. 272-291, Apr. 2018. (pdf)
  8. M. Abavisani and V. M. Patel, “Multimodal sparse and low-rank subspace clustering”, Information Fusion, vol. 39, pp. 168-177, Jan. 2018. (pdf)

 

2017

  1. P. Wang, H. Zhang and V. M. Patel, “SAR image despeckling using a convolutional neural network”, IEEE Signal Processing Letters, vol. 24, no. 12, pp. 1763 – 1767, Dec. 2017. (pdf)
  2. S. Wang, V. M. Patel and A. Petropulu, “The robust sparse Fourier transform and its application in radar signal processing”, IEEE Transactions on Aerospace and Electronic Systems, vol. 53, no. 6, pp. 2735-2755, Dec. 2017.  (pdf)
  3. H. Zhang, V. M. Patel, R. Chellappa, “Low-rank and joint sparse representations for multimodal recognition”, IEEE Transactions on Image Processing, vol. 26, no. 10, pp. 4741-4752, Oct. 2017. (pdf)
  4.  J. Chen, V. M. Patel, V. Kellokumpu, G. Zhao, M. Pietikäinen, and R. Chellappa, “Robust local features for remote face recognition”,Image and Vision Computing, vol. 64, pp. 34-46, 2017. (pdf)
  5. E. Gonzalez-Sosa, R. Vera-Rodriguez, J. Fierrez and V. M. Patel, “Exploring body shape from mmW images for person recognition”,IEEE Transactions on Information Forensics and Security, vol. 12, no.9, pp. 2079-2089, Sept. 2017. (pdf)
  6. H. Zhang and V. M. Patel, “Sparse representation-based open set recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no.8, pp. 1690-1696, Aug. 2017. (pdf)
  7. A. Ghosh, M. A. Powers, and V. M. Patel, “Computational LADAR imaging”, Applied Optics, vol. 56, no. 3, pp. B191-B197, 2017. (link)
  8. X. Gibert-Serra, V. M. Patel, and R. Chellappa, “Deep multi-task learning for railway track inspection”, IEEE Transactions on Intelligent Transportation Systems, vol. 18, no. 1, pp. 153-164, Jan. 2017. (pdf)
  9. P. Samangouei, V. M. Patel, and R. Chellappa, “Facial attributes for active authentication on mobile devices”, Image and Vision Computing, vol. 58, pp. 181-192, Feb. 2017. (pdf)

 

2016

  1. V. M. Patel, J. N. Mait, D. W. Prather, and A. S. Hedden, “Computational millimeter wave imaging: problems, progress and prospects”, IEEE Signal Processing Magazine: Special Issue on Computational Photography and Displays, vol. 33, no. 5, pp. 109-118, Sept. 2016. (pdf)
  2. V. M. Patel, R. Chellappa, D. Chandra, and B. Barbello, “Continuous user authentication on mobile devices: recent progress and remaining challenges”, IEEE Signal Processing Magazine, vol. 33, no. 4, pp. 49-61, July 2016. (pdf)

 

2015

  1. H. V. Nguyen, H. T. Ho, V. M. Patel, and R. Chellappa, “DASH-N: Joint hierarchical domain adaptation and feature learning”, IEEE Transactions on Image Processing, vol. 24, no. 12, pp. 5479 – 5491, Dec. 2015. (pdf)
  2. Y-C. Chen, V. M. Patel, P. J. Phillips, and R. Chellappa, “Dictionary-based face and person recognition from unconstrained video”,IEEE Access: Special Issue on 4D’s of Machine Learning for Biometrics: Deep Learning, Dictionary Learning, Domain Adaptation, and Distance Metric Learning, vol. 3, pp. 1783 – 1798, Oct. 2015. (pdf)
  3. A. Shrivastava, V. M. Patel, J. K. Pillai, and R. Chellappa, “Generalized dictionaries for multiple instance learning”, International Journal of Computer Vision: Special Issue on Sparse Coding, vol. 114, no. 2, pp. 288-305, Sept. 2015. (pdf)
  4. V. M. Patel, N. K. Ratha, and R. Chellappa, “Cancelable biometrics: A review”, IEEE Signal Processing Magazine: Special Issue on Biometric Security and Privacy, vol. 32, no. 5, pp. 54-65, Sept. 2015. (pdf)
  5. S. Shekhar, V. M. Patel, H. V. Nguyen and R. Chellappa, “Coupled projections for adaptation of dictionaries”, IEEE Transactions on Image Processing, vol 24, no. 10, pp. 2941-2954, Oct. 2015. (pdf)
  6. R. Gopalan, R. Li, V. M. Patel and R. Chellappa, “Domain adaptation for visual recognition”, Foundations and Trends on Computer Graphics and Vision, vol. 8, no. 4, pp 285-378, Mar. 2015. (pdf)
  7. A. Shrivastava, J. K. Pillai, and V. M. Patel, “Multiple kernel-based dictionary learning for weakly supervised classification”, Pattern Recognition, vol. 48, no. 8, pp. 2667-2675, Aug. 2015. (pdf)
  8. V. M. Patel, H. V. Nguyen, and R. Vidal, “Latent space sparse and low-rank subspace clustering”, IEEE Journal of Selected Topics in Signal Processing: Special Issue on Signal Processing for Big Data, vol. 9, no. 4, pp. 691-701, June 2015. (pdf)
  9. Y-C. Chen, V. M. Patel, R. Chellappa, and P. J. Phillips, “Salient views and view-dependent dictionaries for object recognition”,Pattern Recognition: Special Issue on Discriminative Feature Learning from Big Data for Visual Recognition, vol. 48, no. 10, pp. 3053 – 3066, Oct. 2015. (pdf)
  10. V. M. Patel, R. Gopalan, R. Li, and R. Chellappa, “Visual domain adaptation: a survey of recent advances”, IEEE Signal Processing Magazine, vol. 32, no. 3, pp. 53 – 69, May 2015. (pdf)
  11. A. Shrivastava, V. M. Patel, and R. Chellappa, “Non-linear dictionary learning with partially labeled data”, Pattern Recognition, vol. 48, no. 11, pp. 283-3292, Nov. 2015. (pdf)

 

2014

  1. Y-C. Chen, V. M. Patel, R. Chellappa, and P. J. Phillips, “Ambiguously labeled learning using dictionaries”, IEEE Transactions on Information Forensics and Security: Special Issue on Facial Biometrics in the Wild, vol. 9, no. 12, pp. 2076-2088, Dec. 2014. (pdf)
  2. Q. Qiu, V. M. Patel, and R. Chellappa, “Information-theoretic dictionary learning for image classification”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 36, no. 11, pp. 2173-2184, Oct. 2014. (pdf)