To date, I have published 3 PAMI, 1 IJCV, 5 NIPS, 1 ICLR, 10 CVPR, 6 ICCV, 4 ECCV, 2 MM, 3 ICDM, 1 IROS, 1 ICRA, 1 CDC, 38 in total. All my publications can be downloaded from my Google Scholar profile. Please send me an email with any problem.
2024
P94. Xihan Ma, Mingjie Zeng, Jeffrey C. Hill, Beatrice Hoffmann, Ziming Zhang, and Haichong K. Zhang. Guiding the Last Centimeter: Novel Anatomy-Aware Probe Servoing for Standardized Imaging Plane Navigation in Robotic Lung Ultrasound. In IEEE Transactions on Automation Science and Engineering (TASE), 2024.
P93. Fangzhou Lin*, Haotian Liu*, Haoying Zhou*, Songlin Hou*, Kazunori D Yamada, Gregory S. Fischer, Yanhua Li, Haichong K. Zhang, and Ziming Zhang. Loss Distillation via Gradient Matching for Point Cloud Completion with Weighted Chamfer Distance. In Proceeding of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024. (oral)
P92. Guanyi Mo, Yun Yue, Kyumin Lee, and Ziming Zhang. Wildlife Product Trading in Online Social Networks: A Case Study on Ivory-Rlated Product Sales Promotion Posts. In Proceeding of International AAAI COnference on Web and Social Media (ICWSM), 2024.
P91. Kaifeng Zhang, Rui Zhao, Ziming Zhang, and Yang Gao. Auto-Encoding Adversarial Imitation Learning. In Proceeding of International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2024.
P90. Rabeeh Majidi, Vahid Entezari, Ziming Zhang, and Ali Kiapour. Tailored Shoulder Rehabilitation: Patient-specific Sizing Of Ai-driven Wearable Brace Forenhanced Orthopedic Care. In Proceeding of Orthopaedic Research Society (ORS) Annual Meeting, 2024.
P89. Yun Yue, Fangzhou Lin, Guanyi Mou, and Ziming Zhang. Understanding Hyperbolic Metric Learning through Hard Negative Sampling. In Proceeding of Winter Conference on Applications of Computer Vision (WACV), 2024.
2023
P88. Ziming Zhang, Kaidong Li, and Guanghui Wang. Robust Structured Declarative Classifiers for Point Clouds. In World Scientific Annual Review of Artificial Intelligence, 2023.
P87. Biao Yin, Nicholas Josselyn, Thomas Considine, John Kelley, Berend Rinderspacher, Robert Jensen, James Snyder, Ziming Zhang, and Elke Rundensteiner. DeepSC-Edge: Scientific Corrosion Segmentation with Edge-Guided and Class-Balanced Losses. In Proceeding of IEEE International Conference on Machine Learning and Applications (ICMLA), 2023.
P86. Fangzhou Lin*, Yun Yue*, Ziming Zhang, Songlin Hou, Kazunori Yamada, Vijaya B. Kolachalama, and Venkatesh Saligrama. InfoCD: A Contrastive Chamfer Distance Loss for Point Cloud Completion. In Proceeding of Advances in Neural Information Processing Systems (NeurIPS), 2023.
P85. Biao Yin, Nicholas Josselyn, Ziming Zhang, Elke Rundensteiner, Thomas Considine, John Kelley, Berend Rinderspacher, Robert Jensen and James Snyder. MOSS: AI Platform for Discovery of Corrosion-Resistant Materials. In Proceeding of The 32nd ACM International Conference on Information and Knowledge Management (CIKM), 2023.
P84. Fangzhou Lin, Yun Yue, Songlin Hou, Xuechu Yu, Yajun Xu, Kazunori D Yamada, and Ziming Zhang. Hyperbolic Chamfer Distance for Point Cloud Completion. In Proceeding of International Conference on Computer Vision (ICCV), 2023.
P83. Evan Emil Sauter, Maqsood Ali Mughal, and Ziming Zhang. Evaluation of Machine Learning Methods on Large-Scale Spatio-temporal Data for Photovoltaic Power Prediction. In Energies, 2023.
P82. M. Caner Tol, Saad Islam, Andrew J. Adiletta, Berk Sunar, and Ziming Zhang. Don’t Knock! Rowhammer at the Backdoor of DNN Models. In Proceeding of The 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Network (IEEE IFIP DSN), 2023.
P81. Yiqing Zhang, Xinming Huang, and Ziming Zhang. PRISE: Demystifying Deep Lucas-Kanade with Strongly Star-Convex Constraints for Multimodel Image Alignment. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2023. (a highlight paper)
P80. Yingxue Zhang, Yanhua Li, Xun Zhou, Ziming Zhang, and Jun Luo. STM-GAIL: Spatial-Temporal Meta-GAIL for Learning Diverse Human Driving Strategies. In Proceeding of SIAM International Conference on Data Mining (SDM), 2023.
P79. Xin Zhang, Yanhua Li, Ziming Zhang, and Zhi-Li Zhang. Domain Disentangled Meta-Learning. In Proceeding of SIAM International Conference on Data Mining (SDM), 2023.
P78. Xin Zhang, Yanhua Li, Ziming Zhang, Christopher G. Brinton, Zhenming Liu, and Zhi-Li Zhang. Distributional Cloning for Stabilized Imitation Learning via ADMM. In IEEE International Conference on Data Mining (ICDM), pp. 818-827, 2023.
P77. Rabeeh Majidi, Mehdi Ghasemi, Ziming Zhang, Edward A. Clancy, Vahid Entezari, and Ali Kiapour. AI-based Wearable Device For Tracking Shoulder Joint Kinematics And Muscle Activity In Subjects With Fshd Disease. In Proceeding of Orthopaedic Research Society (ORS) Annual Meeting, 2023.
P76. Rabeeh Majidi, Vahid Entezari, Ziming Zhang, Edward A. Clancy, and Ali Kiapour. Ai-based Wireless Sensor System For Tracking Muscle Activity And Kinematics Of The Shoulder Joint. In Proceeding of Orthopaedic Research Society (ORS) Annual Meeting, 2023. (PODIUM presentation)
P75. Guojun Wu, Xin Zhang, Ziming Zhang, Yanhua Li, Xun Zhou, Christopher Brinton, and Zhenming Liu. Learning Lightweight Neural Networks via Channel-Split Recurrent Convolution. In Proceeding of Winter Conference on Applications of Computer Vision (WACV), 2023.
P74. Keshav Bimbraw, Christopher Nycz, Matthew Schueler, Ziming Zhang, and Haichong Zhang. Simultaneous Estimation of Hand Configurations and Finger Joint Angles using Forearm Ultrasound. In IEEE Transactions on Medical Robotics and Bionics, 2023.
2022
P73. Nicholas Josselyn, Biao Yin, Ziming Zhang, and Elke Rundensteiner. An Empirical Study of Domain Adaptation: Are We Really Learning Transferable Representations? In Proceeding of IEEE International Conference on Big Data Special session MLBD, 2022.
P72. Nicholas Josselyn, Biao Yin, Thomas Considine, John Kelley, Berend Rinderspacher, Robert Jensen, James Snyder, Ziming Zhang, and Elke Rundensteiner. Transferring Indoor Corrosion Image Assessment Models to Outdoor Images via Domain Adaptation. In Proceeding of IEEE International Conference on Machine Learning and Applications (ICMLA), 2022.
P71. Rebecca Dollahite*, Kevin Wang*, Kaidong Li, Yiqing Zhang, and Ziming Zhang. Verifying Adversarial Robustness of 3D Object Detectors for Autonomous Vehicles. In Proceeding of IEEE MIT Undergraduate Research Technology Conference, 2022.
P70. Yichen Ding, Ziming Zhang, Yanhua Li, and Xun Zhou. EgoSpeed-Net: Forecasting Speed-Control in Driver Behavior from Egocentric Video Data. In Proceeding of ACM SIGSPATIAL, 2022. (oral)
P69. Mahdi Elhousni, Ziming Zhang, and Xinming Huang. LiDAR-OSM-Based Vehicle Localization in GPS-Denied Environments by Using Constrained Particle Filter. In Sensors, 2022.
P68. Chengxin Liu, Kewei Wang, Hao Lu, Zhiguo Cao, and Ziming Zhang. Robust Object Detection with Inaccurate Bounding Boxes. In Proceeding of European Conference on Computer Vision (ECCV), 2022.
P67. R. Majidi, A. Kiapour, V. Entezari, M. Ghasemi, Z. Zhang and E. Clancy. Artificial Intelligence Based Muscle Activity and Muscle Monitoring Tracker with Wireless Sensor System. In Proceeding of the Twenty Fourth Congress of the International Society of Electrophysiology and Kinesiology, Quebec City, PQ, Canada, 22–25 June, 2022.
P66. Fangzhou Lin, Yajun Xu, Ziming Zhang, Chenyang Gao, and Kazunori D Yamada. Cosmos Propagation Network: Deep Learning Model for Point Cloud Completion. In Neurocomputing, 2022.
P65. Kaidong Li*, Ziming Zhang*, Cuncong Zhong, and Guanghui Wang. Robust Structured Declarative Classifiers for 3D Point Clouds: Defending Adversarial Attacks with Implicit Gradients. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2022.
P64. Shuaiyuan Du, Chaoyi Hong, Yinpeng Chen, Zhiguo Cao, and Ziming Zhang. Class-attribute inconsistency learning for novelty detection. In Pattern Recognition, 2022.
P63. Keshav Bimbraw, Christopher J Nycz, Matthew Schueler, Ziming Zhang, and Haichong Zhang. Prediction of Metacarpophalangeal joint angles and Classification of Hand configurations based on Ultrasound Imaging of the Forearm. In Proceeding of IEEE International Conference on Robotics and Automation (ICRA), 2022.
P62. Yecheng Lyu, Xinming Huang, and Ziming Zhang. EllipsoidNet: Ellipsoid Representation for Point Cloud Classification and Segmentation. In Proceeding of Winter Conference on Applications of Computer Vision (WACV), 2022.
2021
P61. Ming Li, Jun Liu, Ce Zheng, Xinming Huang, and Ziming Zhang. Exploiting Multi-view Part-wise Correlation via an Efficient Transformer for Vehicle Re-Identification. In IEEE Transactions on Multimedia (TMM), 2021.
P60. Yiming Zhao, Mahdi Elhousni, Ziming Zhang, and Xinming Huang. Distance Transform Pooling Neural Network for LiDAR Depth Completion. In IEEE Transactions on Neural Networks and Learning Systems, 2021.
P59. Biao Yin, Nicholas Josselyn, Thomas Considine, John Kelley, Berend Rinderspacher, Robert Jensen, James Snyder, Ziming Zhang, and Elke Rundensteiner. Corrosion Image Data Set for Automating Scientific Assessment of Materials. In Proceeding of British Machine Vision Conference (BMVC), 2021.
P58. Mahdi Elhousni, Ziming Zhang, and Xinming Huang. Height Prediction and Refinement from Aerial Images with Semantic and Geometric Guidance. In IEEE Access, 2021.
P57. Ziming Zhang, Yun Yue, Guojun Wu, Yanhua Li, and Haichong Zhang. SBO-RNN: Reformulating Recurrent Neural Networks via Stochastic Bilevel Optimization. In Proceeding of Advances in Neural Information Processing Systems (NeurIPS), 2021.
P56. Johnathan Adams, Ziming Zhang, Gregory Noetscher, Ara Nazarian, and Sergey Makarov. Application of a Neural Network Classifier to Radiofrequency-Based Osteopenia/Osteoporosis Screening. In IEEE Journal of Translational Engineering in Health and Medicine, 2021.
P55. Ziming Zhang, Guojun Wu, Yun Yue, Yanhua Li, and Xun Zhou. Deep Incremental RNN for Learning Sequential Data: A Lyapunov Stable Dynamical System. In Proceeding of IEEE International Conference on Data Mining (ICDM), 2021.
P54. Xin Zhang, Yanhua Li, Xun Zhou, Oren Mangoubi, Ziming Zhang, Vincent Filardi, and Jun Luo. DAC-ML: Domain Adaptable Continuous Meta-Learning for Urban Dynamics Prediction. In Proceeding of IEEE International Conference on Data Mining (ICDM), 2021.
P53. Xin Zhang, Weixiao Huang, Yanhua Li, Renjie Liao, and Ziming Zhang. Imitation Learning From Inconcurrent Multi-Agent Interactions. In Proceeding of IEEE Conference on Decision and Control (CDC), 2021.
P52. Ming Li, Xinming Huang, and Ziming Zhang. Self-supervised Geometric Features Discovery with Interpretable Attention for Vehicle Re-Identification and Beyond. In Proceeding of International Conference on Computer Vision (ICCV), 2021.
P51. Johnathan Adams, Ziming Zhang, Gregory Noetscher, Ara Nazarian, and Sergey Makarov. Application of a Neural Network Classifier to Radiofrequency-Based Osteopenia/Osteoporosis Screening. In Proceeding of 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021.
P50. Xihan Ma, Ziming Zhang, and Haichong Zhang. Autonomous Scanning Target Localization for Robotic Lung Ultrasound Imaging. In Proceeding of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021.
P49. Surya Murugavel Ravishankar, Ryosuke Tsumura, John Hardin, Beatrice Hoffmann, Ziming Zhang, and Haichong K. Zhang. Anatomical Feature-Based Lung Ultrasound Image Assessment Using Deep Convolutional Neural Network. In Proceeding of IEEE International Ultrasonics Symposium (IUS), 2021.
P48. Yiming Zhao, Xinming Huang, and Ziming Zhang. Deep Lucas-Kanade Homography for Multimodal Image Alignment. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2021.
P47. Yecheng Lyu, Xinming Huang, and Ziming Zhang. Revisiting 2D Convolutional Neural Networks for Graph-based Applications. IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
P46. Yiming Zhao, Lin Bai, Ziming Zhang, and Xinming Huang. A Surface Geometry Model for LiDAR Depth Completion. IEEE Robotics and Automation Letters, 2021.
2020
P45. Feiyun Cui, Yun Yue, Yi Zhang, Ziming Zhang, and H. Susan Zhou. Advancing Biosensors with Machine Learning. ACS Sensors, 2020.
P44. Ziming Zhang. An Efficient Empirical Solver for Localized Multiple Kernel Learning via DNNs. In Proceeding of International Conference on Pattern Recognition (ICPR), 2020.
P43. Yun Yue, Ming Li, Venkatesh Saligrama, and Ziming Zhang. RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm. In Proceeding of International Conference on Pattern Recognition (ICPR), 2020.
P42. Yecheng Lyu, Ming Li, Xinming Huang, Ulkuhan Guler, Patrick Schaumont, and Ziming Zhang. TreeRNN: Topology-Preserving Deep Graph Embedding and Learning. In Proceeding of International Conference on Pattern Recognition (ICPR), 2020.
P41. Xin Zhang, Yanhua Li, Ziming Zhang, and Zhi-Li Zhang. f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning. In Proceeding of Advances in Neural Information Processing Systems (NeurIPS), 2020.
P40. Xin Zhang, Yanhua Li, Xun Zhou, Ziming Zhang, and Jun Luo. TrajGAIL: Trajectory Generative Adversarial Imitation Learning for Long-term Decision Analysis. In Proceeding of International Conference on Data Mining (ICDM), 2020.
P39. Keshav Bimbraw, Xihan Ma, Ziming Zhang, and Haichong Zhang. Augmented Reality-Based Lung Ultrasound Scanning Guidance. In Proceeding of Workshop on Advances in Simplifying Medical UltraSound (ASMUS), Medical Image Computing and Computer Assisted Intervention (MICCAI) 2020.
P38. Ce Zheng, Yecheng Lyu, Ming Li, and Ziming Zhang. LodoNet: A Deep Neural Network with 2D Keypoint Matching for 3D LiDAR Odometry Estimation. In Proceeding of ACM International Conference on Multimedia (ACM MM), 2020.
P37. Yecheng Lyu, Xinming Huang, and Ziming Zhang. Learning to Segment 3D Point Clouds in 2D Image Space. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2020. (oral) Demo code
P36. Anil Kag, Ziming Zhang, and Venkatesh Saligrama. RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients? In Proceeding of International Conference on Learning Representations (ICLR), 2020.
P35. Ziming Zhang, Wenchi Ma, Yuanwei Wu, and Guanghui Wang. Self-Orthogonality Module: A Network Architecture Plug-in for Learning Orthogonal Filters. In Proceeding of Winter Conference on Applications of Computer Vision (WACV), 2020.
P34. Wenju Xu, Guanghui Wang, Alan Sullivan, and Ziming Zhang. Towards Learning Affine-Invariant Representations via Data-Efficient CNNs. In Proceeding of Winter Conference on Applications of Computer Vision (WACV), 2020.
P33. Mahdi Elhousni, Yecheng Lyu, Xinming Huang, and Ziming Zhang. Automatic Building and Labeling of HD Maps with Deep Learning. In Proceeding of Thirty-Second Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), 2020.
2019
P32. Yao Sui, Ziming Zhang, Guanghui Wang, Yafei Tang, and Li Zhang. Exploiting the Anisotropy of Correlation Filter Learning for Visual Tracking. International Journal of Computer Vision (IJCV), 2019.
P31. Yuanwei Wu, Ziming Zhang, and Guanghui Wang. Unsupervised Deep Feature Transfer for Low Resolution Image Classification. In Proceeding of Workshop and Challenge on Real-World Recognition from Low-Quality Images and Videos, International Conference on Computer Vision (ICCV), 2019.
2018
P30. Jian Zheng, Teng-Yok Lee, Chen Feng, Xiaohua Li, and Ziming Zhang. Robust Attentional Pooling via Feature Selection. In Proceeding of International Conference on Pattern Recognition (ICPR), 2018.
P29. Ziming Zhang*, Yuanwei Wu*, and Guanghui Wang. BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2018.
2017
P28. Ziming Zhang, Yun Liu, Xi Chen, Yanjun Zhu, Ming-Ming Cheng, Venkatesh Saligrama, and Philip H.S. Torr. Sequential Optimization for Efficient High-Quality Object Proposal Generation. IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI), 2017.
P27. Ziming Zhang, and Matthew Brand. Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks. In Proceeding of Advances in Neural Information Processing Systems (NIPS), 2017.
P26. Chiori Hori, Takaaki Hori, Teng-Yok Lee, Ziming Zhang, Bret Harsham, John R. Hershey, Tim K. Marks, and Kazuhiro Sumi. Attention-Based Multimodel Fusion for Video Description. In Proceeding of International Conference on Computer Vision (ICCV), 2017.
2016
P25. Ziming Zhang, and Philip H.S. Torr. Object Proposal Generation using Two-Stage Cascade SVMs. IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
P24. Ziming Zhang, and Venkatesh Saligrama. PRISM: Person Re-Identification via Structured Matching. IEEE Transaction on Circuits and Systems for Video Technology (TCSVT), June 2016.
P23. Ziming Zhang, and Venkatesh Saligrama. Zero-Shot Recognition via Structured Prediction. In Proceeding of European Conference on Computer Vision (ECCV), 2016.
P22. Yao Sui, Ziming Zhang, Guanghui Wang, Yafei Tang, and Li Zhang. Real-Time Visual Tracking: Promoting the Robustness of Correlation Filter Learning. In Proceeding of European Conference on Computer Vision (ECCV), 2016.
P21. Ziming Zhang, Yuting Chen, and Venkatesh Saligrama. Efficient Training of Very Deep Neural Networks for Supervised Hashing. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2016.
P20. Ziming Zhang, and Venkatesh Saligrama. Zero-Shot Learning via Joint Latent Similarity Embedding. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2016.
2015
P19. Ziming Zhang, and Venkatesh Saligrama. Zero-Shot Learning via Semantic Similarity Embedding. In Proceeding of International Conference on Computer Vision (ICCV), 2015.
P18. Ziming Zhang, Yuting Chen, and Venkatesh Saligrama. Group Membership Prediction. In Proceeding of International Conference on Computer Vision (ICCV), 2015.
P17. Gregory D. Castanon, Yuting Chen, Ziming Zhang, and Venkatesh Saligrama. Efficient Activity Retrieval through Semantic Graph Queries. In Proceeding of ACM International Conference on Multimedia (ACM MM), 2015: 391-400. (oral)
P16. Ziming Zhang, and Venkatesh Saligrama. RAPID: Rapidly Accelerated Proximal Gradient Algorithms for Convex Minimization. In Proceeding of International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015.
2014
P15. Ziming Zhang, Heng Huang, and Dinggang Shen. Integrative Analysis of Multi-Dimensional Imaging Genomics Data for Alzheimer’s Disease Prediction. Frontiers in Aging Neuroscience, 2014.
P14. Ziming Zhang, Yuting Chen, and Venkatesh Saligrama. A Novel Visual Word Co-occurrence Model for Person Re-identification In ECCV Workshop on Visual Surveillance and Re-Identification, 2014.
P13. Ming-Ming Cheng, Ziming Zhang, Wen-Yan Lin, and Philip H.S. Torr. BING: Binarized normed gradients for objectness estimation at 300fps. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2014. (oral)
2012
P12. Ziming Zhang, Paul Sturgess, Sunando Sengupta, Nigel Crook, and Philip H.S. Torr. Efficient Discriminative Learning of Parametric Nearest Neighbor Classifiers. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2012.
2011
P11. Ziming Zhang, Lubor Ladicky, Philip H.S. Torr, and Amir Saffari. Learning Anchor Planes for Classification. In Proceeding of Advances in Neural Information Processing Systems (NIPS), 2011: 1611-1619.
P10. Ziming Zhang, Jonathan Warrell, and Philip H.S. Torr. Proposal Generation for Object Detection using Cascaded ranking SVMs. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2011: 1497-1504.
P9. Ziming Zhang, Jiawei Huang, and Ze-Nian Li. Learning Sparse Features On-Line for Image Classification. In Proceeding of International Conference on Image Analysis and Recognition (ICIAR), 2011: 122-131. (oral)
2010
P8. Ziming Zhang, Jiawei Huang, and Ze-Nian Li. Discovering Motion Patterns for Human Action Recognition. In Proceeding of Pacific-Rim Conference on Multimedia (PCM), 2010: 716-727.
P7. Ziming Zhang, Ze-Nian Li, and Mark Drew. Learning Image Similarities via Probabilistic Feature Matching. In Proceeding of International Conference on Image Processing (ICIP), 2010: 1857-1860. (oral)
P6. Ziming Zhang, Ze-Nian Li, and Mark Drew. AdaMKL: A Novel Biconvex Multiple Kernel Learning Approach. In Proceeding of International Conference on Pattern Recognition (ICPR), 2010: 2126-2129. (oral)
2009
P5. Ziming Zhang, Ze-Nian Li, and Mark Drew. Feature Correspondence with Constrained Global Structures. In Proceeding of International Conference on Image Processing (ICIP), 2009: 177-180.
2008
P4. Ziming Zhang, Yiqun Hu, Syin Chan, and Liang-Tien Chia. Motion Context: A New Representation for Human Action Recognition. In Proceeding of European Conference on Computer Vision (ECCV), 2008: 817-829.
2007
P3. Ziming Zhang, Syin Chan, and Liang-Tien Chia. Image Classification Using Tensor Representation. In Proceeding of ACM International Conference on Multimedia (MM), 2007: 281-284.
P2. Ziming Zhang, Syin Chan, and Liang-Tien Chia. Discriminative Signatures for Image Classification. In Proceeding of International Conference on Image Processing (ICIP), 2007: 197-200.
P1. Ziming Zhang, Syin Chan, and Liang-Tien Chia. Codebook+: A New Module for Creating Discriminative Codebooks. In Proceeding of International Conference on Multimedia and Expo (ICME), 2007: 815-818.