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Faculty of Engineering

The Chair

Profile photo of Dr Q. M. Jonathan Wu

Dr. Q. M. Jonathan Wu

Professor

Department of Electrical and Computer Engineering
University of Windsor
401 Sunset Avenue
Windsor, Ontario, N9B 3P4, Canada

519-253-3000 ext. 2580
Office: 3034 CEI
jwu@uwindsor.ca

Q. M. Jonathan Wu (M’92–SM’09) received the Ph.D. degree in electrical engineering from the University of Wales, Swansea, U.K., in 1990. He was with the National Research Council of Canada for ten years from 1995, where he became a Senior Research Officer and a Group Leader. He is currently a Professor with the Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada. He has published more than 300 peer-reviewed papers in computer vision, image processing, intelligent systems, robotics, and integrated microsystems. His current research interests include machine learning, 3-D computer vision, video content analysis, interactive multimedia, sensor analysis and fusion, and visual sensor networks.
Dr. Wu holds the Tier 1 Canada Research Chair in Automotive Sensors and Information Systems. He was Associate Editor for IEEE Transactions on Systems, Man, and Cybernetics Part A, and the International Journal of Robotics and Automation. Currently, he is an Associate Editor for the IEEE Transaction on Neural Networks and Learning Systems and the Journal of Cognitive Computation. He has served on technical program committees and international advisory committees for many prestigious conferences.

View the complete list of publications

  1. L. Zhang, C. Shi, J. Niu, Y. Ji, Q. M. J. Wu, DOA estimation for HFSWR target based on PSO-ELM, IEEE Geosci. Remote. Sens. Lett. 19 (2022) 1–5.
  2. W. Zhang, Q. M. J. Wu, Y. Yang, T. Akilan, W. G. W. Zhao, Q. Li, J. Niu, Fast ship detection with spatial-frequency analysis and anova-based feature fusion, IEEE Geosci. Remote. Sens.Lett. 19 (2022) 1–5.
  3. J. Zhao, Z. Chen, Q. M. J. Wu, X. Li, L. Cai, K. Zhu, Improved edge-guided network for single image super-resolution, Multim. Tools Appl. 81 (1) (2022) 343–365.
  4. W. Zhang, Q. M. J. Wu, Y. Yang, T. Akilan, M. Li, HKPM: A hierarchical key-area perception model for HFSWR maritime surveillance, IEEE Trans. Geosci. Remote. Sens. 60 (2022) 1–13.
  5. H. Zhang, Z. Liang, C. Li, H. Zhong, L. Liu, C. Zhao, Y. Wang, Q. M. J. Wu, A practical robotic grasping method by using 6-d pose estimation with protective correction, IEEE Trans. Ind. Electron. 69 (4) (2022) 3876–3886.
  6. L. Yan, C. Di, Q. M. J. Wu, Y. Xia, Sequential fusion for multirate multisensor systems with heavy-tailed noises and unreliable measurements, IEEE Trans. Syst. Man Cybern. Syst. 52 (1) (2022) 523–532.
  7. W. Pan, Z. Zhou, M. Ling, X. Geng, Q. M. J. Wu, Learning hierarchical graph representation for image manipulation detection, CoRR abs/2201.05730. arXiv:2201.05730.
  8. C. Yuan, Q. Cui, X. Sun, Q. M. J. Wu, S. Wu, Chapter five - fingerprint liveness detection using an improved CNN with the spatial pyramid pooling structure, Adv. Comput. 120 (2021) 157–193.
  9. X. Xu, Y. Li, Q. M. J. Wu, A compact multi-pattern encoding descriptor for texture classification, Digit. Signal Process. 114 (2021) 103081.
  10. Z. Zhou, M. Wang, C. Yang, Z. Fu, X. Sun, Q. M. J. Wu, Blockchain-based decentralized reputation system in e-commerce environment, Future Gener. Comput. Syst. 124 (2021) 155–167.
  11. Z. Zhou, W. Pan, Q. M. J. Wu, C. Yang, Z. Lv, Geometric rectification-based neural network architecture for image manipulation detection, Int. J. Intell. Syst. 36 (12) (2021) 6993–7016.
  12. H. Wang, Y. Sun, Q. M. J. Wu, X. Lu, X. Wang, Z. Zhang, Self-supervised monocular depth estimation with direct methods, Neurocomputing 421 (2021) 340–348.
  13. K. Li, D. Shi, Y. Zhang, Q. M. J.Wu, X. Luan, D. Song, Cascnet: No-reference saliency quality assessment with cascaded applicability sorting and comparing network, Neurocomputing 425 (2021) 231–242.
  14. X. Feng, Q. M. J. Wu, Y. Yang, L. Cao, A compensation-based optimization strategy for top dense layer training, Neurocomputing 453 (2021) 563–578.
  15. H. Wang, Q. M. J. Wu, D. Wang, J. Xin, Y. Yang, K. Yu, Echo state network with a global reversible autoencoder for time series classification, Inf. Sci. 570 (2021) 744–768.
  16. K. Zhu, Z. Chen, Q. M. J. Wu, N. Wang, J. Zhao, G. Zhang, FSFN: feature separation and fusion network for single image super-resolution, Multim. Tools Appl. 80 (21) (2021) 31599–31618.
  17. X. Yan, Z. Chen, Q. M. J.Wu, M. Lu, L. Sun, 3mnet: Multi-task, multi-level and multi-channel feature aggregation network for salient object detection, Mach. Vis. Appl. 32 (2) (2021) 45.
  18. A. M. Rafi, T. I. Tonmoy, U. Kamal, Q. M. J. Wu, M. K. Hasan, Remnet: remnant convolutional neural network for camera model identification, Neural Comput. Appl. 33 (8) (2021) 3655–3670.
  19. A. N. Paul, P. Yan, Y. Yang, H. Zhang, S. Du, Q. M. J. Wu, Non-iterative online sequential learning strategy for autoencoder and classifier, Neural Comput. Appl. 33 (23) (2021) 16345–16361.
  20. L. Zhang, J. Zhang, J. Niu, Q. M. J. Wu, G. Li, Track prediction for HF radar vessels submerged in strong clutter based on MSCNN fusion with GRU-AM and AR model, Remote. Sens. 13 (11) (2021) 2164.
  21. M. Wu, L. Zhang, J. Niu, Q. M. J. Wu, Target detection in clutter/interference regions based on deep feature fusion for HFSWR, IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 14 (2021) 5581–5595.
  22. W. Wu, Q. M. J. Wu, W. Sun, Y. Yang, X. Yuan, W. Zheng, B. Lu, A regression method with subnetwork neurons for vigilance estimation using EOG and EEG, IEEE Trans. Cogn. Dev. Syst. 13 (1) (2021) 209–222.
  23. W. Wu, W. Sun, Q. M. J. Wu, C. Zhang, Y. Yang, H. Yu, B. Lu, Faster single model vigilance detection based on deep learning, IEEE Trans. Cogn. Dev. Syst. 13 (3) (2021) 621–630.
  24. Z. Zhou, Q. M. J. Wu, X. Sun, Multiple distance-based coding: Toward scalable feature matching for large-scale web image search, IEEE Trans. Big Data 7 (3) (2021) 559–573.
  25. L. Sun, Z. Chen, Q. M. J. Wu, H. Zhao, W. He, X. Yan, Ampnet: Average- and max-pool networks for salient object detection, IEEE Trans. Circuits Syst. Video Technol. 31 (11) (2021) 4321–4333.
  26. T. Bouraffa, L. Yan, Z. Feng, B. Xiao, Q. M. J. Wu, Y. Xia, Context-aware correlation filter learning toward peak strength for visual tracking, IEEE Trans. Cybern. 51 (10) (2021) 5105–5115.
  27. K. Yang, L. Zhang, J. Niu, Y. Ji, Q. M. J. Wu, Analysis and estimation of shipborne HFSWR target parameters under the influence of platform motion, IEEE Trans. Geosci. Remote. Sens.59 (6) (2021) 4703–4716.
  28. S. Duan, Z. Chen, Q. M. J. Wu, L. Cai, D. Lu, Multi-scale gradients self-attention residual learning for face photo-sketch transformation, IEEE Trans. Inf. Forensics Secur. 16 (2021) 1218–1230.
  29. W. Zhang, Q. M. J.Wu, Y. Yang, T. Akilan, H. Zhang, A width-growth model with subnetwork nodes and refinement structure for representation learning and image classification, IEEE Trans. Ind. Informatics 17 (3) (2021) 1562–1572.
  30. Y. Chen, H. Zhang, Y. Wang, Y. Yang, X. Zhou, Q. M. J. Wu, MAMA net: Multi-scale attention memory autoencoder network for anomaly detection, IEEE Trans. Medical Imaging 40 (3) (2021) 1032–1041.
  31. Y. Ji, H. Zhang, Z. Jie, L. Ma, Q. M. J. Wu, CASNet: A cross-attention siamese network for video salient object detection, IEEE Trans. Neural Networks Learn. Syst. 32 (6) (2021) 2676–2690.
  32. T. Wang, J. Cao, X. Lai, Q. M. J. Wu, Hierarchical one-class classifier with within-class scatter-based autoencoders, IEEE Trans. Neural Networks Learn. Syst. 32 (8) (2021) 3770–3776.
  33. W. Zhang, Q. M. J. Wu, Y. Yang, T. Akilan, Multimodel feature reinforcement framework using Moore-Penrose inverse for big data analysis, IEEE Trans. Neural Networks Learn. Syst. 32 (11) (2021) 5008–5021.
  34. A. K. Singh, Q. M. J. Wu, A. Al-Haj, C. Pu, Introduction to the special section on security and privacy of medical data for smart healthcare, ACM Trans. Internet Techn. 21 (3) (2021) 53:1–53:4.
  35. W. Zhang, Q. M. J. Wu, Y. Yang, W. G. W. Zhao, H. Zhang, Multi-model least squares-based recomputation framework for large data analysis, CoRR abs/2101.01271. arXiv:2101.01271.
  36. Y. Yang, W. Zhang, Q. M. J. Wu, W. G. W. Zhao, A. Chen, Deconvolution-and-convolution networks, CoRR abs/2103.11887. arXiv:2103.11887.
  37. Y. Chen, H. Zhang, Y.Wang, Q. M. J.Wu, Y. Yang, Projected sliced Wasserstein autoencoder based hyperspectral images anomaly detection, CoRR abs/2112.11243. arXiv:2112.11243.
  38. L. Zhang, Q. Li, Q. M. J. Wu, Target detection for HFSWR based on an s3d algorithm, IEEE Access 8 (2020) 224825–224836.
  39. X. Xu, Y. Li, Q. M. J. Wu, A completed local shrinkage pattern for texture classification, Appl. Soft Comput. 97 (Part B) (2020) 106830.
  40. X. Xu, Y. Li, Q. M. J. Wu, A multiscale hierarchical threshold-based completed local entropy binary pattern for texture classification, Cogn. Comput. 12 (1) (2020) 224–237.
  41. Y. Cao, Z. Zhou, Q. M. J. Wu, C. Yuan, X. Sun, Coverless information hiding based on the generation of anime characters, EURASIP J. Image Video Process. 2020 (1) (2020) 36.
  42. H. Zhang, H. Guo, X. Wang, Y. Ji, Q. M. J. Wu, Clothescounter: A framework for star-oriented clothes mining from videos, Neurocomputing 377 (2020) 38–48.
  43. X. Feng, Q. M. J. Wu, Y. Yang, L. Cao, An autoencoder-based data augmentation strategy for generalization improvement of DCNNs, Neurocomputing 402 (2020) 283–297.
  44. W. Zhang, Q. M. J. Wu, Y. Yang, Wi-hsnn: A subnetwork-based encoding structure for dimension reduction and food classification via harnessing multi-CNN model high-level features, Neurocomputing 414 (2020) 57–66.
  45. C. Yuan, X. Chen, P. Yu, R. Meng, W. Cheng, Q. M. J. Wu, X. Sun, Semi-supervised stacked autoencoder-based deep hierarchical semantic feature for real-time fingerprint liveness detection, J. Real-Time Image Process. 17 (1) (2020) 55–71.
  46. H. Wang, Q. M. J. Wu, J. Xin, J. Wang, H. Zhang, Optimizing deep belief echo state network with a sensitivity analysis input scaling auto-encoder algorithm, Knowl. Based Syst. 191 (2020)105257.
  47. Y. Wang, Z. Chen, Q. M. J. Wu, X. Rong, Deep mutual learning network for gait recognition, Multim. Tools Appl. 79 (31-32) (2020) 22653–22672.
  48. M.Wang, Z. Chen, Q. M. J.Wu, M. Jian, Improved face super-resolution generative adversarial networks, Mach. Vis. Appl. 31 (4) (2020) 22.
  49. Z. Li, Z. Chen, Q. M. J. Wu, C. Liu, Pedestrian detection via deep segmentation and context network, Neural Comput. Appl. 32 (10) (2020) 5845–5857.
  50. Y. Yang, Q. M. J. Wu, X. Feng, T. Akilan, Recomputation of the dense layers for performance improvement of DCNN, IEEE Trans. Pattern Anal. Mach. Intell. 42 (11) (2020) 2912–2925.
  51. L. Zhang, D. Mao, J. Niu, Q. M. J. Wu, Y. Ji, Continuous tracking of targets for stereoscopic HFSWR based on IMM filtering combined with ELM, Remote. Sens. 12 (2) (2020) 272.
  52. D. Zhu, J. Niu, M. Li, L. Zhang, Y. Ji, Q. M. J. Wu, Motion parameter identification and motion compensation for shipborne HFSWR by using the reference RF signal generated at the shore, Remote. Sens. 12 (17) (2020) 2807.
  53. C. Yuan, Z. Xia, X. Sun, Q. M. J. Wu, Deep residual network with adaptive learning framework or fingerprint liveness detection, IEEE Trans. Cogn. Dev. Syst. 12 (3) (2020) 461–473.
  54. X. Li, Z. Chen, Q. M. J. Wu, C. Liu, 3d parallel fully convolutional networks for real-time video wildfire smoke detection, IEEE Trans. Circuits Syst. Video Technol. 30 (1) (2020) 89–103.
  55. H. Zhang, Y. Sun, M. Zhao, T. W. S. Chow, Q. M. J. Wu, Bridging user interest to item content for recommender systems: An optimization model, IEEE Trans. Cybern. 50 (10) (2020) 4268–4280.
  56. Z. Zhou, Q. M. J. Wu, S. Wan, W. Sun, X. Sun, Integrating SIFT and CNN feature matching for partial-duplicate image detection, IEEE Trans. Emerg. Top. Comput. Intell. 4 (5) (2020) 593–604.
  57. X. Jin, Y.Wang, H. Zhang, H. Zhong, L. Liu, Q. M. J.Wu, Y. Yang, DM-RIS: deep multimodel rail inspection system with improved MRF-GMM and CNN, IEEE Trans. Instrum. Meas. 69 (4) (2020) 1051–1065.
  58. H. Zhang, M. Zhao, L. Liu, H. Zhong, Z. Liang, Y. Yang, X. Zhou, Q. M. J.Wu, Y.Wang, Deep multimodel cascade method based on CNN and random forest for pharmaceutical particle detection, IEEE Trans. Instrum. Meas. 69 (9) (2020) 7028–7042.
  59. T. Akilan, Q. J. Wu, A. Safaei, J. Huo, Y. Yang, A 3d CNN-LSTM-based image-to-image foreground segmentation, IEEE Trans. Intell. Transp. Syst. 21 (3) (2020) 959–971.
  60. A. Thangarajah, Q. M. J. Wu, SENDEC: An improved image to image CNN for foreground localization, IEEE Trans. Intell. Transp. Syst. 21 (10) (2020) 4435–4443.
  61. Z. Zhou, Q. M. J. Wu, Y. Yang, X. Sun, Region-level visual consistency verification for largescale partial-duplicate image search, ACM Trans. Multim. Comput. Commun. Appl. 16 (2) (2020) 54:1–54:25.
  62. W. Zhang, Y. Yang, Q. M. J. Wu, Deep networks with fast retraining, CoRR abs/2008.07387. arXiv:2008.07387.
  63. A. M. Rafi, S. Rana, R. Kaur, Q. M. J. Wu, P. M. Zadeh, Understanding global reaction to the recent outbreaks of COVID-19: insights from Instagram data analysis, CoRR abs/2009.06862. arXiv:2009.06862.
  64. C. Yuan, Z. Xia, L. Jiang, Y. Cao, Q. M. J. Wu, X. Sun, Fingerprint liveness detection using an improved CNN with image scale equalization, IEEE Access 7 (2019) 26953–26966.
  65. H. Zhang, Y. Chen, Y. Song, Z. Xiong, Y. Yang, Q. M. J. Wu, Automatic kidney lesion detection for CT images using morphological cascade convolutional neural networks, IEEE Access 7 (2019) 83001–83011.
  66. Q. Cui, Z. Zhou, Z. Fu, R. Meng, X. Sun, Q. M. J. Wu, Image steganography based on foreground object generation by generative adversarial networks in mobile edge computing with internet of things, IEEE Access 7 (2019) 90815–90824.
  67. B. Xiao, Y. Du, Q. M. J. Wu, Q. Xu, L. Yan, A fast hybrid model for large-scale zero-shot image recognition based on knowledge graphs, IEEE Access 7 (2019) 119309–119318.
  68. Z. Zhou, Y. Cao, M. Wang, E. Fan, Q. M. J. Wu, Faster-RCNN based robust coverless information hiding system in cloud environment, IEEE Access 7 (2019) 179891–179897.
  69. W. Zhang, Q. Li, Q. M. J. Wu, Y. Yang, M. Li, A novel ship target detection algorithm based on error self-adjustment extreme learning machine and cascade classifier, Cogn. Comput. 11 (1) (2019) 110–124.
  70. G. Bhatnagar, Q. M. J. Wu, A fractal dimension based framework for night vision fusion, IEEE CAA J. Autom. Sinica 6 (1) (2019) 220–227.
  71. Y. Ji, H. Zhang, K. Tseng, T. W. S. Chow, Q. M. J. Wu, Graph model-based salient object detection using objectness and multiple saliency cues, Neurocomputing 323 (2019) 188–202.
  72. L. Liu, H. Zhang, Y. Ji, Q. M. J. Wu, Toward AI fashion design: An attribute-gan model for clothing match, Neurocomputing 341 (2019) 156–167.
  73. H. Wang, Q. M. J. Wu, J. Wang, W. Wu, K. Yu, Optimizing simple deterministically constructed cycle reservoir network with a redundant unit pruning auto-encoder algorithm, Neurocomputing 356 (2019) 184–194.
  74. E. Mohammadi, Q. M. J. Wu, M. Saif, Y. Yang, Hierarchical feature representation for unconstrained video analysis, Neurocomputing 363 (2019) 182–194.
  75. D. Lu, Z. Chen, Q. M. J. Wu, X. Zhang, FCN based preprocessing for exemplar-based face sketch synthesis, Neurocomputing 365 (2019) 113–124.
  76. D. Zhao, Z. Chen, Q. M. J. Wu, C. Liu, Two-stage local details restoration framework for face hallucination, Mach. Vis. Appl. 30 (1) (2019) 153–162.
  77. C. Li, Z. Chen, Q. M. J. Wu, C. Liu, Saliency object detection: integrating reconstruction and prior, Mach. Vis. Appl. 30 (3) (2019) 397–406.
  78. K. Wang, Z. Chen, Q. M. J. Wu, C. Liu, Face recognition using AMVP and WSRC under variable illumination and pose, Neural Comput. Appl. 31 (8) (2019) 3805–3818.
  79. Z. Li, Z. Chen, Q. M. J. Wu, C. Liu, Real-time pedestrian detection with deep supervision in the wild, Signal Image Video Process. 13 (4) (2019) 761–769.
  80. Z. Zhou, Y. Mu, Q. M. J. Wu, Coverless image steganography using partial-duplicate image retrieval, Soft Comput. 23 (13) (2019) 4927–4938.
  81. C. Yuan, X. Sun, Q. M. J. Wu, Difference co-occurrence matrix using BP neural network for fingerprint liveness detection, Soft Comput. 23 (13) (2019) 5157–5169.
  82. A. Safaei, Q. M. J. Wu, A. Thangarajah, Y. Yang, System-on-a-chip (soc)-based hardware acceleration for an online sequential extreme learning machine (OS-ELM), IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38 (11) (2019) 2127–2138.
  83. B. Youssefi, A. J. Leigh, M. Mirhassani, Q. M. J. Wu, Tunable neuron with PWL approximation based on the minimum operator, IEEE Trans. Circuits Syst. II Express Briefs 66-II (2) (2019) 387–391.
  84. X. Zhang, Z. Chen, Q. M. J.Wu, L. Cai, D. Lu, X. Li, Fast semantic segmentation for scene perception, IEEE Trans. Ind. Informatics 15 (2) (2019) 1183–1192.
  85. S. Soltanpour, Q. J. Wu, Weighted extreme sparse classifier and local derivative pattern for 3d face recognition, IEEE Trans. Image Process. 28 (6) (2019) 3020–3033.
  86. C. Li, Z. Chen, Q. M. J. Wu, C. Liu, Deep saliency with channel-wise hierarchical feature responses for traffic sign detection, IEEE Trans. Intell. Transp. Syst. 20 (7) (2019) 2497–2509.
  87. Y. Yang, Q. M. J. Wu, Features combined from hundreds of midlayers: Hierarchical networks with subnetwork nodes, IEEE Trans. Neural Networks Learn. Syst. 30 (11) (2019) 3313–3325.
  88. A. Thangarajah, Q. M. J. Wu, W. Zhang, Video foreground extraction using multi-view receptive field and encoder-decoder DCNN for traffic and surveillance applications, IEEE Trans. Veh. Technol. 68 (10) (2019) 9478–9493.
  89. A. Thangarajah, Q. J. Wu, H. Zhang, Effect of fusing features from multiple DCNN architectures in image classification, IET Image Process. 12 (7) (2018) 1102–1110.
  90. G. Huang, Q. M. J. Wu, D. C. W. II, Hierarchical extreme learning machines, Neurocomputing 277 (2018) 1–3.
  91. Y. Ji, H. Zhang, Q. M. J. Wu, Saliency detection via conditional adversarial image-to-image network, Neurocomputing 316 (2018) 357–368.
  92. C. Li, Z. Chen, Q. M. J. Wu, C. Liu, Deep saliency detection via channel-wise hierarchical feature responses, Neurocomputing 322 (2018) 80–92.
  93. Y. Ji, H. Zhang, Q. M. J. Wu, Salient object detection via multi-scale attention CNN, Neurocomputing 322 (2018) 130–140.
  94. A. Thangarajah, Q. M. J. Wu, Y. Yang, Fusion-based foreground enhancement for background subtraction using multivariate multi-model gaussian distribution, Inf. Sci. 430 (2018) 414–431.
  95. A. Safaei, Q. M. J. Wu, Y. Yang, System-on-a-chip (soc)-based hardware acceleration for foreground and background identification, J. Frankl. Inst. 355 (4) (2018) 1888–1912. 
  96. Z. K. Malik, A. Hussain, Q. M. J. Wu, Extracting online information from dual and multiple data streams, Neural Comput. Appl. 30 (1) (2018) 87–98.
  97. J. Huo, Q. M. J. Wu, J. Cao, G. Wang, Supervoxel based method for multi-atlas segmentation of brain MR images, NeuroImage 175 (2018) 201–214.
  98. Z. Zhou, Q. M. J. Wu, X. Sun, Encoding multiple contextual clues for partial-duplicate image retrieval, Pattern Recognit. Lett. 109 (2018) 18–26.
  99. L. Zhang, W. You, Q. M. J. Wu, S. Qi, Y. Ji, Deep learning-based automatic clutter/interference detection for HFSWR, Remote. Sens. 10 (10) (2018) 1517.
  100. Y. Peng, Z. Chen, Q. M. J. Wu, C. Liu, Traffic flow detection and statistics via improved optical flow and connected region analysis, Signal Image Video Process. 12 (1) (2018) 99–105.
  101. G. Li, L. Zeng, L. Zhang, Q. M. J. Wu, State identification of duffing oscillator based on extreme learning machine, IEEE Signal Process. Lett. 25 (1) (2018) 25–29.
  102. Y. Yang, Q. M. J. Wu, W. Zheng, B. Lu, Eeg-based emotion recognition using hierarchical network with subnetwork nodes, IEEE Trans. Cogn. Dev. Syst. 10 (2) (2018) 408–419.
  103. H. Zhang, X. Li, H. Zhong, Y. Yang, Q. M. J. Wu, J. Ge, Y. Wang, Automated machine vision system for liquid particle inspection of pharmaceutical injection, IEEE Trans. Instrum. Meas. 67 (6) (2018) 1278–1297.
  104. H. Zhang, X. Jin, Q. M. J. Wu, Y. Wang, Z. He, Y. Yang, Automatic visual detection system of railway surface defects with curvature filter and improved gaussian mixture model, IEEE Trans. Instrum. Meas. 67 (7) (2018) 1593–1608.
  105. H. Zhang, S. Wang, X. Xu, T. W. S. Chow, Q. M. J. Wu, Tree2vector: Learning a vectorial representation for tree-structured data, IEEE Trans. Neural Networks Learn. Syst. 29 (11) (2018) 5304–5318.
  106. Y. Yang, Q. M. J.Wu, Y.Wang, Autoencoder with invertible functions for dimension reduction and image reconstruction, IEEE Trans. Syst. Man Cybern. Syst. 48 (7) (2018) 1065–1079.
  107. Y. Yang, Q. M. J. Wu, X. Feng, A. Thangarajah, Non-iterative recomputation of dense layers for performance improvement of DCNN, CoRR abs/1809.05606. arXiv:1809.05606.
  108. S. Soltanpour, Q. J. Wu, Multimodal 2d-3d face recognition using local descriptors: pyramidal shape map and structural context, IET Biom. 6 (1) (2017) 27–35.
  109. L. Kong, H. Zhang, Y. Zheng, Y. Chen, J. Zhu, Q. J.Wu, Image segmentation using a hierarchical student’s-t mixture model, IET Image Process. 11 (11) (2017) 1094–1102.
  110. Z. Zhou, Q. M. J. Wu, F. Huang, X. Sun, Fast and accurate near-duplicate image elimination for visual sensor networks, Int. J. Distributed Sens. Networks 13 (2).
  111. Q. Li, W. Zhang, M. Li, J. Niu, Q. M. J. Wu, Automatic detection of ship targets based on wavelet transform for HF surface wavelet radar, IEEE Geosci. Remote. Sens. Lett. 14 (5) (2017) 714–718.
  112. S. Soltanpour, B. Boufama, Q. M. J. Wu, A survey of local feature methods for 3d face recognition, Pattern Recognit. 72 (2017) 391–406.
  113. K. Wang, Z. Chen, Q. M. J. Wu, C. Liu, Illumination and pose variable face recognition via adaptively weighted ulbp mhog and WSRC, Signal Process. Image Commun. 58 (2017) 175–186.
  114. Z. K. Malik, A. Hussain, Q. J. Wu, Multilayered echo state machine: A novel architecture and algorithm, IEEE Trans. Cybern. 47 (4) (2017) 946–959.
  115. Z. Zhou, Y. Wang, Q. M. J. Wu, C. Yang, X. Sun, Effective and efficient global context verification for image copy detection, IEEE Trans. Inf. Forensics Secur. 12 (1) (2017) 48–63.
  116. F. Sun, G. Huang, Q. M. J. Wu, S. Song, D. C. W. II, Efficient and rapid machine learning algorithms for big data and dynamic varying systems, IEEE Trans. Syst. Man Cybern. Syst. 47 (10) (2017) 2625–2626.
  117. A. Thangarajah, Q. M. J. Wu, W. Jiang, A feature embedding strategy for high-level CNN representations from multiple convnets, CoRR abs/1705.04301. arXiv:1705.04301.
  118. Z. Zhou, C. Yang, B. Chen, X. Sun, Q. Liu, Q. M. J. Wu, Effective and efficient image copy detection with resistance to arbitrary rotation, IEICE Trans. Inf. Syst. 99-D (6) (2016) 1531–1540.
  119. S. K. Vipparthi, S. Murala, A. B. Gonde, Q. M. J. Wu, Local directional mask maximum edge patterns for image retrieval and face recognition, IET Comput. Vis. 10 (3) (2016) 182–192.
  120. Y. Chen, J. Li, H. Zhang, Y. Zheng, B. Jeon, Q. J. Wu, Non-local-based spatially constrained hierarchical fuzzy C-means method for brain magnetic resonance imaging segmentation, IET Image Process. 10 (11) (2016) 865–876.
  121. Z. K. Malik, A. Hussain, Q. M. J. Wu, An online generalized eigenvalue version of Laplacian eigenmaps for visual big data, Neurocomputing 173 (2016) 127–136.
  122. Y. Chen, H. Zhang, Y. Zheng, B. Jeon, Q. M. J.Wu, An improved anisotropic hierarchical fuzzy c-means method based on multivariate student t-distribution for brain MRI segmentation, Pattern Recognit. 60 (2016) 778–792.
  123. A. Saha, Q. M. J. Wu, Full-reference image quality assessment by combining global and local distortion measures, Signal Process. 128 (2016) 186–197.
  124. T. M. Nguyen, Q. J. Wu, A consensus model for motion segmentation in dynamic scenes, IEEE Trans. Circuits Syst. Video Technol. 26 (12) (2016) 2240–2249.
  125. Y. Yang, Q. M. J. Wu, Multilayer extreme learning machine with subnetwork nodes for representation learning, IEEE Trans. Cybern. 46 (11) (2016) 2570–2583. .
  126. Y. Yang, Q. M. J. Wu, Extreme learning machine with subnetwork hidden nodes for regression and classification, IEEE Trans. Cybern. 46 (12) (2016) 2885–2898.
  127. T. M. Nguyen, Q. M. J. Wu, Online feature selection based on fuzzy clustering and its applications, IEEE Trans. Fuzzy Syst. 24 (6) (2016) 1294–1306.
  128. T. Chen, Y. Wang, C. Xiao, Q. M. J. Wu, A machine vision apparatus and method for can-end inspection, IEEE Trans. Instrum. Meas. 65 (9) (2016) 2055–2066.
  129. T. M. Nguyen, Q. M. J. Wu, Multiple kernel point set registration, IEEE Trans. Medical Imaging 35 (6) (2016) 1381–1394. doi:10.1109/TMI.2015.2511063.
  130. H. Zhang, T. W. S. Chow, Q. M. J. Wu, Organizing books and authors by multilayer SOM, IEEE Trans. Neural Networks Learn. Syst. 27 (12) (2016) 2537–2550.
  131. G. Wang, J. S. Zelek, Q. M. J. Wu, R. Bajcsy, Robust structure from motion in the presence of outliers and missing data, CoRR abs/1609.02638. arXiv:1609.02638.
  132. A. Hussain, D. Tao, Q. M. J. Wu, D. Zhao, Computational intelligence for changing environments [guest editorial], IEEE Comput. Intell. Mag. 10 (4) (2015) 10–11.
  133. G. Bhatnagar, Q. M. J. Wu, A novel chaos-based secure transmission of biometric data, Neurocomputing 147 (2015) 444–455.
  134. S. Murala, Q. M. J. Wu, Spherical symmetric 3d local ternary patterns for natural, texture and biomedical image indexing and retrieval, Neurocomputing 149 (2015) 1502–1514.
  135. G. Bhatnagar, Q. M. J. Wu, Z. Liu, A new contrast based multimodal medical image fusion framework, Neurocomputing 157 (2015) 143–152.
  136. Y. Zheng, B. Jeon, D. Xu, Q. M. J. Wu, H. Zhang, Image segmentation by generalized hierarchical fuzzy c-means algorithm, J. Intell. Fuzzy Syst. 28 (2) (2015) 961–973.
  137. G. Bhatnagar, Q. M. J.Wu, A new robust and efficient multiple watermarking scheme, Multim. Tools Appl. 74 (19) (2015) 8421–8444.
  138. D. Mukherjee, Q. M. J. Wu, G. Wang, A comparative experimental study of image feature detectors and descriptors, Mach. Vis. Appl. 26 (4) (2015) 443–466. .
  139. T. M. Nguyen, Q. M. J. Wu, A non-parametric Bayesian model for bounded data, Pattern Recognit. 48 (6) (2015) 2084–2095.
  140. Y. Wan, Z. Miao, Q. M. J. Wu, X. Wang, Z. Tang, Z. Wang, A quasi-dense matching approach and its calibration application with internet photos, IEEE Trans. Cybern. 45 (3) (2015) 370–383.
  141. Y. Yang, Q. M. J. Wu, Y. Wang, K. M. Zeeshan, X. Lin, X. Yuan, Data partition learning with multiple extreme learning machines, IEEE Trans. Cybern. 45 (8) (2015) 1463–1475.
  142. A. Saha, Q. J. Wu, Utilizing image scales towards totally training free blind image quality assessment, IEEE Trans. Image Process. 24 (6) (2015) 1879–1892.
  143. T. M. Nguyen, Q. M. J. Wu, H. Zhang, Asymmetric mixture model with simultaneous feature selection and model detection, IEEE Trans. Neural Networks Learn. Syst. 26 (2) (2015) 400–408.
  144. Y. Yang, Y.Wang, Q. M. J.Wu, X. Lin, M. Liu, Progressive learning machine: A new approach for general hybrid system approximation, IEEE Trans. Neural Networks Learn. Syst. 26 (9) (2015) 1855–1874.
  145. H. Zhang, T. Wen, Y. Zheng, D. Xu, D. Wang, T. M. Nguyen, Q. M. J. Wu, Two fast and robust modified gaussian mixture models incorporating local spatial information for image segmentation, J. Signal Process. Syst. 81 (1) (2015) 45–58.
  146. Z. K. Malik, A. Hussain, Q. M. J. Wu, Novel biologically inspired approaches to extracting online information from temporal data, Cogn. Comput. 6 (3) (2014) 595–607.
  147. G. Bhatnagar, Q. M. J. Wu, P. K. Atrey, Robust logo watermarking using biometrics inspired key generation, Expert Syst. Appl. 41 (10) (2014) 4563–4578.
  148. H. Zhang, Q. M. J. Wu, T. M. Nguyen, Image segmentation by Dirichlet process mixture model with generalised mean, IET Image Process. 8 (2) (2014) 103–111.
  149. H. Zhang, Q. M. J.Wu, Y. Zheng, T. M. Nguyen, D.Wang, Effective fuzzy clustering algorithm with Bayesian model and mean template for image segmentation, IET Image Process. 8 (10) (2014) 571–581.
  150. G. Bhatnagar, A. Saha, Q. M. J. Wu, P. K. Atrey, Analysis and extension of multiresolution singular value decomposition, Inf. Sci. 277 (2014) 247–262.
  151. S. Murala, Q. M. J. Wu, Expert content-based image retrieval system using robust local patterns, J. Vis. Commun. Image Represent. 25 (6) (2014) 1324–1334.
  152. G. Bhatnagar, Q. M. J. Wu, Enhancing the transmission security of biometric images using chaotic encryption, Multim. Syst. 20 (2) (2014) 203–214.
  153. T. M. Nguyen, Q. M. J. Wu, H. Zhang, Bounded generalized gaussian mixture model, Pattern Recognit. 47 (9) (2014) 3132–3142.
  154. S. Murala, Q. M. J. Wu, MRI and CT image indexing and retrieval using local mesh peak valley edge patterns, Signal Process. Image Commun. 29 (3) (2014) 400–409.
  155. T. M. Nguyen, Q. M. J. Wu, Bounded asymmetrical student’s-t mixture model, IEEE Trans. Cybern. 44 (6) (2014) 857–869.
  156. H. Zhang, Q. M. J. Wu, T. M. Nguyen, X. Sun, Synthetic aperture radar image segmentation by modified student’s t-mixture model, IEEE Trans. Geosci. Remote. Sens. 52 (7) (2014) 4391–4403.
  157. D. Mukherjee, Q. M. J. Wu, T. M. Nguyen, Gaussian mixture model with advanced distance measure based on support weights and histogram of gradients for background suppression, IEEE Trans. Ind. Informatics 10 (2) (2014) 1086–1096.
  158. T. M. Nguyen, Q. J. Wu, An unsupervised feature selection dynamic mixture model for motion segmentation, IEEE Trans. Image Process. 23 (3) (2014) 1210–1225.
  159. T. M. Nguyen, Q. M. J. Wu, D. Mukherjee, H. Zhang, A bayesian bounded asymmetric mixture model with segmentation application, IEEE J. Biomed. Health Informatics 18 (1) (2014) 109–119.
  160. S. Murala, Q. M. J. Wu, Local mesh patterns versus local binary patterns: Biomedical image indexing and retrieval, IEEE J. Biomed. Health Informatics 18 (3) (2014) 929–938.
  161. G. Bhatnagar, Q. M. J. Wu, Biometric inspired multimedia encryption based on dual parameter fractional Fourier transform, IEEE Trans. Syst. Man Cybern. Syst. 44 (9) (2014) 1234–1247.
  162. Z. Wang, Z. Miao, Q. M. J. Wu, Y. Wan, Z. Tang, Low-resolution face recognition: a review, Vis. Comput. 30 (4) (2014) 359–386.
  163. Y. Yang, Q. M. J. Wu, G. Huang, Y. Wang, Pulling back error to the hidden-node parameter technology: Single-hidden-layer feedforward network without output weight, CoRR abs/1405.1445. arXiv:1405.1445.
  164. A. Saha, Q. M. J. Wu, Full-reference image quality assessment by combining global and local distortion measures, CoRR abs/1412.5488. arXiv:1412.5488.
  165. A. Saha, Q. M. J. Wu, High-frequency content based stimulus for perceptual sharpness assessment in natural images, CoRR abs/1412.5490. arXiv:1412.5490.
  166. M. Subrahmanyam, Q. M. J. Wu, R. P. Maheshwari, R. Balasubramanian, Modified color motif co-occurrence matrix for image indexing and retrieval, Comput. Electr. Eng. 39 (3) (2013) 762–774.
  167. A. Saha, G. Bhatnagar, Q. M. J. Wu, Mutual spectral residual approach for multi-focus image fusion, Digit. Signal Process. 23 (4) (2013) 1121–1135.
  168. G. Bhatnagar, Q. M. J. Wu, Z. Liu, Human visual system inspired multi-modal medical image fusion framework, Expert Syst. Appl. 40 (5) (2013) 1708–1720.
  169. T. M. Nguyen, Q. M. J. Wu, A fuzzy logic model based Markov random field for medical image segmentation, Evol. Syst. 4 (3) (2013) 171–181.
  170. G. Bhatnagar, Q. M. J. Wu, Biometrics inspired watermarking based on a fractional dual-tree complex wavelet transform, Future Gener. Comput. Syst. 29 (1) (2013) 182–195.
  171. H. Zhang, Q. M. J. Wu, T. M. Nguyen, Image segmentation by a new weighted student’s t-mixture model, IET Image Process. 7 (3) (2013) 240–251.
  172. H. Zhang, Q. J. Wu, T. M. Nguyen, Modified student’s t-hidden Markov model for pattern recognition and classification, IET Signal Process. 7 (3) (2013) 219–227.
  173. S. Murala, Q. M. J. Wu, Local ternary co-occurrence patterns: A new feature descriptor for MRI and CT image retrieval, Neurocomputing 119 (2013) 399–412.
  174. H. Zhang, Q. M. J. Wu, T. M. Nguyen, Variational Bayes and localized feature selection for student’s t-mixture models, Int. J. Pattern Recognit. Artif. Intell. 27 (6).
  175. G. Bhatnagar, Q. M. J. Wu, B. Raman, Discrete fractional wavelet transform and its application to multiple encryption, Inf. Sci. 223 (2013) 297–316.
  176. G. Bhatnagar, Q. M. J. Wu, A new logo watermarking based on redundant fractional wavelet transform, Math. Comput. Model. 58 (1-2) (2013) 204–218.
  177. G. Bhatnagar, Q. M. J. Wu, B. Raman, A new aspect in robust digital watermarking, Multim. Tools Appl. 66 (2) (2013) 179–200.
  178. A. Baradarani, Q. M. J. Wu, M. Ahmadi, An efficient illumination invariant face recognition framework via illumination enhancement and dd-dtCwt filtering, Pattern Recognit. 46 (1) (2013) 57–72.
  179. T. M. Nguyen, Q. M. J. Wu, D. Mukherjee, H. Zhang, A finite mixture model for detail-preserving image segmentation, Signal Process. 93 (11) (2013) 3171–3181.
  180. A. Saha, Q. M. J. Wu, Perceptual image quality assessment using phase deviation sensitive energy features, Signal Process. 93 (11) (2013) 3182–3191.
  181. M. G. Sarwer, Q. M. J. Wu, X. Zhang, Enhanced satd-based cost function for mode selection of H.264/AVC intra coding, Signal Image Video Process. 7 (4) (2013) 777–786.
  182. H. Zhang, Q. M. J. Wu, T. M. Nguyen, A robust fuzzy algorithm based on student’s t-distribution and mean template for image segmentation application, IEEE Signal Process. Lett. 20 (2) (2013) 117–120.
  183. T. M. Nguyen, Q. M. J. Wu, Fast and robust spatially constrained gaussian mixture model for image segmentation, IEEE Trans. Circuits Syst. Video Technol. 23 (4) (2013) 621–635.
  184. T. M. Nguyen, Q. M. J. Wu, A nonsymmetric mixture model for unsupervised image segmentation, IEEE Trans. Cybern. 43 (2) (2013) 751–765.
  185. H. Zhang, J. K. L. Ho, Q. M. J. Wu, Y. Ye, Multidimensional latent semantic analysis using term spatial information, IEEE Trans. Cybern. 43 (6) (2013) 1625–1640.
  186. T. M. Nguyen, Q. M. J. Wu, Dynamic fuzzy clustering and its application in motion segmentation, IEEE Trans. Fuzzy Syst. 21 (6) (2013) 1019–1031.
  187. D. Mukherjee, Q. M. J. Wu, T. M. Nguyen, Multiresolution based gaussian mixture model for background suppression, IEEE Trans. Image Process. 22 (12) (2013) 5022–5035.
  188. G. Bhatnagar, Q. M. J. Wu, Z. Liu, Directive contrast based multimodal medical image fusion in NSCT domain, IEEE Trans. Multim. 15 (5) (2013) 1014–1024.
  189. D. Liu, C. Anderson, A. T. Azar, G. Battistelli, E. Bayro-Corrochano, C. Cervellera, D. A. Elizondo, M. Filippone, G. Gnecco, X. Hu, T. Huang, W. Liu, W. Lu, A. M. Madureira, I. Skrjanc, T. Villmann, Q. M. J. Wu, S. Xie, D. Xu, Editorial A successful change from TNN to TNNLS and a very successful year, IEEE Trans. Neural Networks Learn. Syst. 24 (1) (2013) 1–7.
  190. H. Zhang, Q. M. J. Wu, T. M. Nguyen, Incorporating mean template into finite mixture model for image segmentation, IEEE Trans. Neural Networks Learn. Syst. 24 (2) (2013) 328–335.
  191. G. Bhatnagar, Q. M. J. Wu, P. K. Atrey, Secure randomized image watermarking based on singular value decomposition, ACM Trans. Multim. Comput. Commun. Appl. 10 (1) (2013) 4:1–4:21.
  192. G. Bhatnagar, Q. M. J. Wu, B. Raman, Robust gray-scale logo watermarking in wavelet domain, Comput. Electr. Eng. 38 (5) (2012) 1164–1176.
  193. G. Bhatnagar, Q. M. J. Wu, B. Raman, Image and video encryption based on dual space-filling curves, Comput. J. 55 (6) (2012) 667–685. 
  194. G. Bhatnagar, Q. M. J. Wu, B. Raman, A new robust adjustable logo watermarking scheme, Comput. Secur. 31 (1) (2012) 40–58.
  195. G. Bhatnagar, Q. M. J. Wu, Selective image encryption based on pixels of interest and singular value decomposition, Digit. Signal Process. 22 (4) (2012) 648–663.
  196. G. Bhatnagar, Q. M. J. Wu, B. Raman, Fractional dual-tree complex wavelet transform and its application to biometric security during communication and transmission, Future Gener. Comput. Syst. 28 (1) (2012) 254–267.
  197. G. Bhatnagar, Q. M. J. Wu, An image fusion framework based on human visual system in framelet domain, Int. J. Wavelets Multiresolution Inf. Process. 10 (1).
  198. Y. Mo, J. Liu, B. Wang, Q. M. J. Wu, A novel swarm intelligence algorithm and its application in solving wireless sensor networks coverage problems, J. Networks 7 (12) (2012) 2037–2043.
  199. A. Baradarani, Q. M. J. Wu, M. Ahmadi, P. Mendapara, Tunable half-band-pair wavelet filter banks and application to multi-focus image fusion, Pattern Recognit. 45 (2) (2012) 657–671.
  200. H. Zhang, Q. M. J. Wu, T. W. S. Chow, M. Zhao, A two-dimensional neighborhood preserving projection for appearance-based face recognition, Pattern Recognit. 45 (5) (2012) 1866–1876.
  201. R. Minhas, A. A. Mohammed, Q. M. J. Wu, An efficient algorithm for focus measure computation in constant time, IEEE Trans. Circuits Syst. Video Technol. 22 (1) (2012) 152–156.
  202. R. Minhas, A. A. Mohammed, Q. M. J. Wu, Incremental learning in human action recognition based on snippets, IEEE Trans. Circuits Syst. Video Technol. 22 (11) (2012) 1529–1541.
  203. G. Wang, J. S. Zelek, Q. M. J. Wu, Structure and motion recovery based on spatial-and temporal-weighted factorization, IEEE Trans. Circuits Syst. Video Technol. 22 (11) (2012) 1590–1603.
  204. G. Bhatnagar, Q. M. J. Wu, Chaos-based security solution for fingerprint data during communication and transmission, IEEE Trans. Instrum. Meas. 61 (4) (2012) 876–887.
  205. W. Zhang, Q. M. J. Wu, G. Wang, X. You, Tracking and pairing vehicle headlight in night scenes, IEEE Trans. Intell. Transp. Syst. 13 (1) (2012) 140–153.
  206. T. M. Nguyen, Q. M. J. Wu, Robust student’s-t mixture model with spatial constraints and its application in medical image segmentation, IEEE Trans. Medical Imaging 31 (1) (2012) 103–116.
  207. T. M. Nguyen, Q. M. J.Wu, Gaussian-mixture-model-based spatial neighborhood relationships for pixel labeling problem, IEEE Trans. Syst. Man Cybern. Part B 42 (1) (2012) 193–202.
  208. G. Bhatnagar, Q. M. J. Wu, B. Raman, A new fractional random wavelet transform for fingerprint security, IEEE Trans. Syst. Man Cybern. Part A 42 (1) (2012) 262–275.
  209. T. M. Nguyen, Q. M. J. Wu, Dirichlet Gaussian mixture model: Application to image segmentation, Image Vis. Comput. 29 (12) (2011) 818–828.
  210. G. Bhatnagar, Q. M. J. Wu, B. Raman, A robust security framework for 3d images, J. Vis. 14 (1) (2011) 85–93.
  211. R. Minhas, A. A. Mohammed, Q. M. J. Wu, Shape from focus using fast discrete curvelet transform, Pattern Recognit. 44 (4) (2011) 839–853.
  212. A. A. Mohammed, R. Minhas, Q. M. J. Wu, M. A. Sid-Ahmed, Human face recognition based on multidimensional PCA and extreme learning machine, Pattern Recognit. 44 (10-11) (2011) 2588–2597.
  213. H. Zhang, H. Shu, G. Coatrieux, J. Zhu, Q. M. J. Wu, Y. Zhang, H. Zhu, L. Luo, Affine Legendre moment invariants for image watermarking robust to geometric distortions, IEEE Trans. Image Process. 20 (8) (2011) 2189–2199.
  214. S. Wong, C. Chen, Q. M. J. Wu, Low power chien search for BCH decoder using rt-level power management, IEEE Trans. Very Large Scale Integr. Syst. 19 (2) (2011) 338–341.
  215. W. Zhang, Q. M. J. Wu, H. B. Yin, Moving vehicles detection based on adaptive motion histogram, Digit. Signal Process. 20 (3) (2010) 793–805.
  216. A. A. Mohammed, R. Minhas, Q. M. J. Wu, M. A. Sid-Ahmed, An efficient fingerprint image compression technique based on wave atoms decomposition and multistage vector quantization, Integr. Comput. Aided Eng. 17 (1) (2010) 29–40.
  217. G. Wang, Q. M. J. Wu, Quasi-perspective projection model: Theory and application to structure and motion factorization from uncalibrated image sequences, Int. J. Comput. Vis. 87 (3) (2010) 213–234.
  218. R. Minhas, A. A. Mohammed, Q. M. J. Wu, A fast recognition framework based on extreme learning machine using hybrid object information, Neurocomputing 73 (10-12) (2010) 1831–1839.
  219. R. Minhas, A. Baradarani, S. Seifzadeh, Q. M. J. Wu, Human action recognition using extreme learning machine based on visual vocabularies, Neurocomputing 73 (10-12) (2010) 1906–1917.
  220. Z. Ji, Q. M. J. Wu, An improved artificial immune algorithm with application to multiple sensor systems, Inf. Fusion 11 (2) (2010) 174–182.
  221. M. J. Islam, Q. M. J. Wu, M. Ahmadi, M. A. Sid-Ahmed, Investigating the performance of naive- Bayes classifiers and K- nearest neighbor classifiers, J. Convergence Inf. Technol. 5 (2) (2010) 133–137.
  222. W. Zhang, Q. M. J. Wu, G. Wang, X. You, Y. Wang, Image matching using enclosed region detector, J. Vis. Commun. Image Represent. 21 (4) (2010) 271–282.
  223. G. Wang, Q. M. J. Wu, The quasi-perspective model: Geometric properties and 3d reconstruction, Pattern Recognit. 43 (5) (2010) 1932–1942.
  224. W. Zhang, Q. M. J. Wu, G. Wang, H. B. Yin, An adaptive computational model for salient object detection, IEEE Trans. Multim. 12 (4) (2010) 300–316.
  225. T. M. Nguyen, Q. M. J. Wu, S. Ahuja, An extension of the standard mixture model for image segmentation, IEEE Trans. Neural Networks 21 (8) (2010) 1326–1338.
  226. G. Wang, H. Tsui, Q. M. J. Wu, What can we learn about the scene structure from three orthogonal vanishing points in images, Pattern Recognit. Lett. 30 (3) (2009) 192–202.
  227. T. Mandal, Q. M. J. Wu, Y. Yuan, Curvelet based face recognition via dimension reduction, Signal Process. 89 (12) (2009) 2345–2353.
  228. M. G. Sarwer, Q. M. J. Wu, Efficient two-step edge-based partial distortion search for fast block motion estimation, IEEE Trans. Consumer Electron. 55 (4) (2009) 2154–2162.
  229. M. G. Sarwer, Q. M. J. Wu, Adaptive variable block-size early motion estimation termination algorithm for H.264/AVC video coding standard, IEEE Trans. Circuits Syst. Video Technol. 19 (8) (2009) 1196–1201.
  230. G. Wang, Q. M. J. Wu, Perspective 3-d euclidean reconstruction with varying camera parameters, IEEE Trans. Circuits Syst. Video Technol. 19 (12) (2009) 1793–1803.
  231. L. Sabeti, E. Parvizi, Q. M. J. Wu, Visual tracking using color cameras and time-of-flight range imaging sensors, J. Multim. 3 (2) (2008) 28–36.
  232. G. Wang, H. Tsui, Q. M. J. Wu, Rotation constrained power factorization for structure from motion of nonrigid objects, Pattern Recognit. Lett. 29 (1) (2008) 72–80.
  233. G. Wang, Q. M. J. Wu, Z. Ji, Single view-based pose estimation from circle or parallel lines, Pattern Recognit. Lett. 29 (7) (2008) 977–985.
  234. G. Wang, Q. M. J. Wu, W. Zhang, Kruppa equation-based camera calibration from homography induced by remote plane, Pattern Recognit. Lett. 29 (16) (2008) 2137–2144.
  235. M. G. Sarwer, L. Po, Q. M. J. Wu, Fast sum of absolute transformed difference based intra-mode decision of H.264/AVC video coding standard, Signal Process. Image Commun. 23 (8) (2008) 571–580.
  236. W. Zhang, Q. M. J. Wu, X. Yang, X. Fang, Multilevel framework to detect and handle vehicle occlusion, IEEE Trans. Intell. Transp. Syst. 9 (1) (2008) 161–174.
  237. G. Wang, Q. M. J. Wu, Stratification approach for 3-d euclidean reconstruction of nonrigid objects from uncalibrated image sequences, IEEE Trans. Syst. Man Cybern. Part B 38 (1) (2008) 90–101.
  238. J. Wu, T. Ishihara, Q. M. J. Wu, Davison type integral controllers for time-delay plants using a simplified predictor, Control. Intell. Syst. 35 (3).
  239. W. Zhang, X. Fang, X. Yang, Q. M. J. Wu, Spatiotemporal Gaussian mixture model to detect moving objects in dynamic scenes, J. Electronic Imaging 16 (2) (2007) 023013.
  240. W. Zhang, X. Fang, X. Yang, Q. M. J. Wu, Moving cast shadows detection using ratio edge, IEEE Trans. Multim. 9 (6) (2007) 1202–1214.
  241. A. Jain, C. W. de Silva, Q. J. Wu, Intelligent fusion of sensor data for product quality assessment in a fish cutting machine, Control. Intell. Syst. 32 (2).
  242. A. Zuo, J. Z. Zhang, K. G. Stanley, Q. M. J. Wu, A hybrid stereo feature matching algorithm for stereo vision-based bin picking, Int. J. Pattern Recognit. Artif. Intell. 18 (8) (2004) 1407–1422.
  243. Y. Lu, J. Z. Zhang, Q. M. J. Wu, Z. Li, A survey of motion-parallax-based 3-d reconstruction algorithms, IEEE Trans. Syst. Man Cybern. Part C 34 (4) (2004) 532–548.
  244. J. Z. Zhang, Q. M. J.Wu, W. A. Gruver, Active head tracking based on chromatic shape fitting, Int. J. Pattern Recognit. Artif. Intell. 17 (4) (2003) 529–544.
  245. J. Z. Zhang, Q. M. J. Wu, W. A. Gruver, Correction to ”binocular transfer method for point feature tracking of image sequences”, IEEE Trans. Syst. Man Cybern. Part C 33 (2) (2003) 291.
  246. J. Z. Zhang, Q. M. J. Wu, H. Tsui, W. A. Gruver, Binocular transfer methods for point-feature tracking of image sequences, IEEE Trans. Syst. Man Cybern. Part C 32 (4) (2002) 392–405.
  247. K. G. Stanley, Q. M. J. Wu, C. W. de Silva, Modular neural-visual serving with image compression input, J. Intell. Fuzzy Syst. 10 (1) (2001) 1–11.
  248. J. Z. Zhang, Q. M. J. Wu, A pyramid approach to motion tracking, Real-Time Imaging 7 (6) (2001) 529–544.
  249. M. R. Lee, C. W. de Silva, E. A. Croft, Q. M. J. Wu, Machine vision system for curved surface inspection, Mach. Vis. Appl. 12 (4) (2000) 177–188.
  250. K. G. Stanley, Q. M. J. Wu, W. A. Gruver, Implementation of vision-based planar grasp planning, IEEE Trans. Syst. Man Cybern. Part C 30 (4) (2000) 517–524.
  251. Q. M. J. Wu, C. W. de Silva, Dynamic switching of fuzzy resolution in knowledge-based self-tuning control, J. Intell. Fuzzy Syst. 4 (1) (1996) 75–85.
  252. Q. M. J. Wu, M. G. Rodd, Fast boundary extraction for industrial inspection, Pattern Recognit. Lett. 12 (8) (1991) 483–489.

Wang, G.H.; Wu, Q.M. Jonathan, “Guide to Three Dimensional Structure and Motion Factorization”, Springer, 2010.

  1. Dibyendu Mukherjee, Ashirbani Saha, Q.M. Jonathan Wu, Wei Jiang (2015). Detection  of abandoned objects using gaussian mixture model based background suppression, Surveillance Systems and National Security of the 21st Century: New Developments,111-135, Nova Publishers.
  2. Ashirbani Saha, Gaurav Bhatnagar, Q.M. Jonathan Wu (2015). Saliency based framework for thermal and visual image fusion, Image Fusion: Principles, Technology and Applications, 17-44, Nova Publishers.
  3. Sarwer, M.G.; Wu, Q.M. Jonathan, “Improved Intra Prediction of H.264/AVC”, Effective Video Coding for Multimedia Applications, 39-54, IN-TECH publisher, editor: Sudhakar Radhakrishnan, 2011.
  4. Wang, G.; Wu, Q.M. Jonathan, “3D Euclidean Reconstruction of Structured Scenes from Uncalibrated Images”, 3D Imaging: Theory, Technology and Applications, 275-292, Editors: Emerson H. Duke and Stephen R. Aguirre, Nova Publisher, 2010.
  5. Wang, G.; Wu, Q.M. Jonathan, “Structure Recovery of Non-Rigid Objects under Perspective Projection Based on Power Factorization”, 3D Imaging: Theory, Technology and Applications, 293-311, Editors: Emerson H. Duke and Stephen R. Aguirre, Nova Publisher, 2010.
  6. Tanaya Guha, Q.M. Jonathan Wu (2010). Curvelet Based Feature Extraction. Oravec M. Face Recognition. : 35-46, Intech Open
  7. Sarwer, M.G.; Po, L.M.; Wu, Q.M. Jonathan, “Bit Rate Estimation for Cost Function of H.264/AVC”, Multimedia, 257-281, IN-TECH publisher, Editor(s) - Kazuki Nishi, 2010.
  8. Thanh N.M.; Wu, Q.M. Jonathan, “Fuzzy System with Positive and Negative Rules”, Machine Learning, 173-189, INTECH publisher, Editor(s) - Yagang Zhang, 2010.
  9. Baradarani, A.; Wu, Q.M. Jonathan, “Wavelet-Based Segmentation: From Scalar Wavelets to Dual-Tree Complex Filter Banks”, Pattern Recognition: Recent Advances, 151-166, INTECH publisher, editor: Adam Herout, 2010.
  10. Zhang, W.; Wu, Q.M. Jonathan; Fang, X., “Moving Cast Shadow Detection”, Vision-Systems: Segmentation and Pattern Recognition, 47-59, I-Tech Education and Publishing, Vienna, Austria, Obinata, G.; Dutta, A. (editors), 2007
  11. Bhatnagar, G.; Wu, Q.M. Jonathan; Raman, B., “Distributive Multi-Resolution Transforms Based Framework for Watermarking”, Information Technology for Intellectual Property Protection: Interdisciplinary Advancements, 1-29, IGI Global (formerly Idea Group Inc.), Editor(s) - Hideyasu Sasaki, 2012.
  12. Wu, Q.M. Jonathan; Stanley, K.; Deravi, F.; Liew, D., "Computer Vision,” Encyclopedia of Electrical and Electronics Engineering, J.G. Webster (editor), John Wiley & Sons, Inc., Vol.4, pp.53-69, 1999.
  13. Wu, Q.M. Jonathan; Stanley, K.; 00de Silva, C.W., "Neural Control Systems and Applications,” Intelligent Adaptive Control: Industrial Applications, L.C. Jain and C.W. de Silva (editors), pp.63-104, CRC Press, 1999.
  1.  Grimson, Eric, L, Object Recognition by Computers: The Role of Geometric Constraints, 512, The MIT Press, 1990,
  2. International Journal on Engineering Applications of Artificial Intelligence. Brady, Michael (ed.), Robotics Science, 617, The MIT Press, Cambridge, Massachusetts, 1989, International Journal on Engineering Applications of Artificial Intelligence, 337-339.
  3. Pitman, Muralidhara S, Interpretation of Visual Motion: A Computational Study, 139, Morgan Kaufmann, London/ Calif., 1988, International Journal on Engineering Applications of Artificial Intelligence, 226, A computational study series: Research Notes in Artificial Intelligence.
  4. Cheng, I.; Cortelazzo, G.; Tripathi, S., 3D Online Multimedia: Representation, Manipulation and Transmission, World Scientific, June 23, 2006.