Zhanyu Ma

Dr. Zhanyu Ma has been a Professor at Beijing University of Posts and Telecommunications (BUPT), Beijing, China, since 2019. He received his M.Eng. degree in Signal and Information Processing from BUPT (Beijing University of Posts and Telecommunications), China, and his Ph.D. degree in Electrical Engineering from KTH (Royal Institute of Technology), Sweden, in 2007 and 2011, respectively. From 2012-2013, he has been a Postdoctoral research fellow in the School of Electrical Engineering, KTH, Sweden.From 2014-2019, he has been an associate professor at Beijing University of Posts and Telecommunications. From 2013-2014, he served as a lecturer at Beijing University of Posts and Telecommunications. His research interests include statistical modeling and machine learning related topics with a focus on applications in speech processing, image processing, biomedical signal processing, bioinformatics, and intelligent energy network.

Email:mazhanyu AT bupt.edu.cn

Educational Experience

  • Ph. D., KTH, 2007.09 — 2011.12

Publications

Ph. D. thesis

  • Zhanyu Ma, “Non-Gaussian Statistical Models and Their Applications”, PhD Thesis, KTH-Royal Institute of Technology, Stockholm, Sweden, 2011. Link

Journal papers (*=Corresponding author)

  1. Ruoyi Du, Jiyang Xie, Zhanyu Ma*, Dongliang Chang, Yi-Zhe Song, and Jun Guo, “Progressive Learning of Category-Consistent Multi-Granularity Features for Fine-Grained Visual Classification”, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted. DOI Code
  2. Jiyang Xie, Zhanyu Ma*, Dongliang Chang, Guoqiang Zhang, and Jun Guo, “GPCA: A Probabilistic Framework for Gaussian Process Embedded Channel Attention”, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted. DOI Code
  3. Jiyang Xie, Zhanyu Ma*, Jianjun Lei, Guoqiang Zhang, Jing-Hao Xue, Zheng-Hua Tan, and Jun Guo, “Advanced Dropout: A Model-free Methodology for Bayesian Dropout Optimization”, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted. DOI Code
  4. Jiyang Xie, Zhanyu Ma*, Jing-Hao Xue, Guoqiang Zhang, Jian Sun, Yinhe Zheng, and Jun Guo, “DS-UI: Dual-Supervised Mixture of Gaussian Mixture Models for Uncertainty Inference in Image Recognition”, IEEE Transactions on Image Processing (TIP), accepted. DOI Code
  5. Zhanyu Ma*, Yuping Lai, Jiyang Xie, Deyu Meng, W. Bastiaan Kleijn, Jun Guo, and Jingyi Yu, “Dirichlet Process Mixture of Generalized Inverted Dirichlet Distributions for Positive Vector Data with Extended Variational Inference”, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), accepted. DOI
  6. Zhanyu Ma*, Xiaoou Lu, Jiyang Xie, Zhen Yang*, Jing-Hao Xue, Zheng-Hua Tan, Bo Xiao, and Jun Guo, “On the Comparisons of Decorrelation Approaches for non-Gaussian Neutral Vector Variables”, IEEE Transactions on Neural Network and Learning Systems (TNNLS), accepted. DOI
  7. Ke Zhang, Yurong Guo, Xinsheng Wang, Dongliang Chang, Zhenbing Zhao, Zhanyu Ma*, and Tony X. Han, “Competing Ratio Loss for Discriminative Multi-class Image Classification”, NEUROCOMPUTING, Volume 464, pp. 473-484, November 2021DOI Code
  8. Wei Xu, Dingkang Liang, Yixiao Zheng, Jiahao Xie, and Zhanyu Ma*, “Dilated-Scale-Aware Category-Attention ConvNet for Multi-Class Object Counting”, IEEE Signal Processing Letters, vol. 28, pp. 1570-1574, 2021. DOI Code
  9. Xiaoxu Li, Zhuo Sun, Jing-Hao Xue*, and Zhanyu Ma, “A Concise Review of Recent Few-shot Meta-learning Methods”, NEUROCOMPUTING, vol. 456, pp. 463-468, October 2021. DOI
  10. Xiaoxu Li, Dongliang Chang, Zhanyu Ma*, Zheng-Hua Tan, Jing-Hao
    Xue, Jie Cao, and Jun Guo, “Deep InterBoost Networks for Small-sample Image Classification”, NEUROCOMPUTING, vol. 456, pp. 492-503, October 2021. DOI Code
  11. Peng Xu, Kun Liu, Tao Xiang, Timothy M. Hospedales, Zhanyu Ma*, Jun Guo, and Yi-Zhe Song, “Fine-Grained Instance-Level Sketch-Based Video Retrieval”, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 31, no. 5, pp. 1995-2007, 2021. DOI
  12. Jiyang Xie,Yixiao Zheng, Ruoyi Du, Weiyu Xiong, Yufei Cao, Zhanyu Ma*, Dongpu Cao, and Jun Guo, “Deep Learning-based Computer Visionfor Surveillance in ITS:Evaluation of State-of-the-art Methods”, IEEE Transactions on Vehicular Technology (TVT), vol. 70, no. 4, pp. 3027-3042, April 2021. DOI Code
  13. Xiaoxu Li, Liyun Yu, Xiaochen Yang, Zhanyu Ma*, Jing-Hao Xue, Jie Cao, and Jun Guo, “ReMarNet: Conjoint Relation and Margin Learning for Small-Sample Image Classification”, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 31, no. 4, pp. 1569-1579, 2021. DOI Code
  14. Yifeng Ding, Zhanyu Ma*, Shaoguo Wen, Jiyang Xie, Dongliang Chang, Zhongwei Si, Ming Wu, and Haibin Ling, “AP-CNN: Weakly Supervised Attention Pyramid Convolutional Neural Network for Fine-Grained Visual Classification”, IEEE Transactions on Image Processing (TIP), vol. 30, pp. 2826-2836, 2021. DOI Code
  15. Xiaoxu Li, Jijie Wu, Zhuo Sun, Zhanyu Ma*, Jie Cao, and Jing-Hao Xue, “BSNet: Bi-Similarity Network for Few-shot Fine-grained Image Classification”, IEEE Transactions on Image Processing (TIP), vol. 30, pp. 1318-1331, 2021. DOI Code
  16. Xiaoou Lu, Yangqi Qiao, Rui Zhu*, Guijin Wang, Zhanyu Ma, and Jing-Hao
    Xue, “Generalisations of Stochastic Supervision Models”, Pattern Recognition (PR), Vol. 109, January 2021. DOI
  17. Jianjun Lei, Yuxin Song, Bo Peng*, Zhanyu Ma, Ling Shao, and Yi-Zhe Song, “Semi-Heterogeneous Three-Way Joint Embedding Network for Sketch-Based Image Retrieval”, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 30, no. 9, pp. 3226-3237, Sept. 2020. DOI
  18. Ke Zhang, Na Liu, Xingfang Yuan, Xinyao Guo, Ce Gao, Zhenbing Zhao, and Zhanyu Ma*, “Fine-Grained Age Estimation in the Wild with Attention LSTM Networks”, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 30, no. 9, pp. 3140-3152, Sept. 2020. DOI Code
  19. Zhanyu Ma, Jiyang Xie*, Hailong Li*, Qie Sun*, Fredrik Wallin, Zhongwei Si, and Jun Guo, “Deep Neural Network-based Impacts Analysis of Multimodal Factors on Heat Demand Prediction”,  IEEE Transactions on Big Data (TBD), vol. 6, no. 3, pp. 594-605, Sept., 2020. DOI
  20. Zhanyu Ma*, Jiyang Xie, Yuping Lai, Jalil Taghia, Jing-Hao Xue, and Jun Guo, “Insights into Multiple/Single Lower Bound Approximation for Extended Variational Inference in Non-Gaussian Structured Data Modeling”, IEEE Transactions on Neural Network and Learning Systems (TNNLS), vol. 31, no. 7, pp. 2240-2254, July, 2020. DOI (ESI高被引)
  21. Yupeng Li, Jianhua Zhang*, Zhanyu Ma, and Yu Zhang, “Clustering Analysis in the Wireless Propagation Channel with a variational Gaussian Mixture Model”, IEEE Transactions on Big Data (TBD), Volume 6, Issue 2, Page 223-232, June 2020. DOI
  22. Xiaoxu Li, Dongliang Chang, Zhanyu Ma*, Zheng-Hua Tan, Jing-Hao Xue, Jie Cao, Jingyi Yu, and Jun Guo, “OSLNet: Deep Small-Sample Classification with an Orthogonal Softmax Layer”, IEEE Transactions on Image Processing (TIP), vol. 29, pp. 6482-6495, 2020. DOI Code
  23. Dongliang Chang, Yifeng Ding, Jiyang Xie, Ayan Kumar Bhunia, Xiaoxu Li, Zhanyu Ma*, Ming Wu, Jun Guo, and Yi-Zhe Song, “The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification”, IEEE Transactions on Image Processing (TIP), vol. 29, pp. 4683-4695, 2020. DOI  Code
  24. Qi Qi, Jingyu Wang, Zhanyu Ma*, Haifeng Sun, Yufei Cao, Lingxin Zhang, and Jianxin Liao, “Knowledge-Driven Service offloading Decision for Vehicular Edge Computing: A Deep Reinforcement Learning Approach”, IEEE Transactions on Vehicular Technology (TVT), Volume 68, Issue 5, Page 4192-4203, May 2019. DOI (ESI高被引)
  25. Xiaoxu Li, Liyun Yu, Dongliang Chang, Zhanyu Ma*, and Jie Cao, “Dual Cross-Entropy Loss for Small-Sample Fine-Grained Vehicle Classification”, IEEE Transactions on Vehicular Technology (TVT), Volume 68, Issue 5, Page 4204-4212, May 2019. DOI
  26. Zhanyu Ma, Yifeng Ding*, Shaoguo Wen, Jiyang Xie, Yifeng Jin, Zhongwei Si, and Haining Wang, “Shoe-print image retrieval with multi-part weighted CNN”, IEEE ACCESS,  Page 59728 – 59736, May 2019.  DOI
  27. Zhanyu Ma, Dongliang Chang, Jiyang Xie, Yifeng Ding, Shaoguo Wen, Xiaoxu Li*, Zhongwei Si, and Jun Guo, “Fine-Grained Vehicle Classification with Channel Max Pooling Modified CNNs”, IEEE Transactions on Vehicular Technology (TVT), Volume 68, Issue 4, Page 3224-3233, Apr. 2019. DOI
  28. Min Min, Song Su, Wenrui He, Yiliang Bi, Zhanyu Ma*, and Yan Liu*, “Computer-aided diagnosis of colorectal polyps using linked color imaging colonoscopy to predict histology”, Scientific Reports, Volume 9, Issue 1, Page 1-8, February, 2019. DOI
  29. Zhanyu Ma*, Yuping Lai, W. Bastiaan Kleijn, Liang Wang, and Jun Guo, “Variational Bayesian Learning for Dirichlet Process Mixture of Inverted Dirichlet Distributions in Non-Gaussian Image Feature Modeling”, IEEE Transactions on Neural Network and Learning Systems (TNNLS), Volume 30, Issue 2, Page 449-463, February 2019. DOIESI高被引
  30. Fangyi Zhu, Zhanyu Ma*, Xiaoxu Li, Guang Chen, Jen-Tzung Chien, Jing-Hao Xue, and Jun Guo, “Image-text dual neural network with decision strategy for small-sample image classification”, NEUROCOMPUTING,  Volume 328, Pages 182-188, February 2019. DOIESI高被引
  31. Zhanyu Ma, Hong Yu*, Wei Chen, and Juo Guo, “Short Utterance based Speech Language Identification in Intelligent Vehicles with Time-scale Modifications and Deep Bottleneck Features”, IEEE Transactions on Vehicular Technology (TVT), Volume 68, Issue 1, Page 121-128, Janurary 2019. DOIESI热点、高被引
  32. Rui Zhu, Ziyu Wang, Zhanyu Ma, Guijin Wang, and Jing-Hao Xue, “LRID: A new metric of multi-class imbalance degree based on likelihood-ratio test”, Pattern Recognition Letters (PRL), Vol. 116, Pages 36-42, December 2018. DOI
  33. Hong Yu, Zheng-Hua Tan, Zhanyu Ma*, Rainer Martin, and Jun Guo, “Spoofing Detection in Automatic Speaker Verification Systems Using DNN Classifiers and Dynamic Acoustic Features”, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Vol. 29, No. 40, pp. 4633-4644, October 2018. DOI
  34. Luyao Liu, Yi Zhao, Dongliang Chang, Jiyang Xie, Zhanyu Ma*, Qie Sun*, Hongyi Yin*, and Ronald Wennersten, “Prediction of short-term PV power output and uncertainty analysis”, Applied Energy (APEN), Vol. 228, pp. 700-711, Oct. 2018. DOI
  35. Jiyang Xie, Zeyu Song, Yupeng Li, Yanting Zhang, Hong Yu, Jinnan Zhan, Zhanyu Ma*, Yuanyuan Qiao, Jianhua Zhang, and Jun Guo, “A survey on machine learning-based mobile big data analysis: challenges and applications”, Wireless Communications and Mobile Computing, vol. 2018, Article ID 8738613, 19 pages, 2018. DOI
  36. Xiaoxu Li*, Zhanyu Ma*, Pai Peng, Xiaowei Guo, Feiyue Huang, Xiaojie Wang, and Jun Guo, “Supervised latent Dirichlet allocation with a mixture of sparse softmax”, NEUROCOMPUTING, Vol. 312, pp. 324-335, Oct. 2018.  DOI
  37. Peng Xu, Qiyue Yin, Yongye Huang, Yi-Zhe Song, Zhanyu Ma*, Liang Wang, Tao Xiang, W. Bastiaan Kleijn, Jun Guo, “Cross-modal Subspace Learning for Fine-grained Sketch-based Image Retrieval”, NEUROCOMPUTING, Vol.278, pp.75-86, Feb. 2018. DOI
  38. Zhanyu Ma*, Jing-Hao Xue, Arne Leijon, Zheng-Hua Tan, Zhen Yang, and Jun Guo, “Decorrelation of Neutral Vector Variables: Theory and Applications”, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Vol. 29, Issue 1, pp. 129-143, Jan. 2018. DOIESI热点、高被引
  39. Zhanyu Ma, Jiyang Xie, Hailong Li*, Qie Sun*, Zhongwei Si, Jianhua Zhang, and Jun Guo, “The Role of Data Analysis in the Development of Intelligent Energy Networks”, IEEE Network, Vol. 31, Issue 5, pp. 88 – 95, 2017. DOI
  40. Xiaochuan Ma, Jianhua Zhang*, Yuxiang Zhang, and Zhanyu Ma, “Data scheme-based wireless channel modeling method: motivation, principle and performance“, Journal of Communications and Information Networks, Vol. 2, Iss. 3, pp. 41-51, September 2017. DOI
  41. Hong Yu, Zheng-Hua Tan, Yiming Zhang, Zhanyu Ma*, and Jun Guo, “DNN Filter Bank Cepstral Coefficients for Spoofing Detection”, IEEE ACCESS, Vol.5, pp. 4779 – 4787, March 2017. DOI
  42. Zhanyu Ma, Hong Yu*, Zheng-Hua Tan, and Jun Guo, “Text-Independent Speaker Identification Using the Histogram Transform Model”, IEEE ACCESS, Vol. 4, pp. 9733 – 9739, Jan. 2017. DOI
  43. Qie Sun, Hailong Li*, Zhanyu Ma*, Chao Wang, Javier Campillo, Fredrik Wallin, and Jun Guo, “A Comprehensive Review of Smart Energy Meters in Intelligent Energy Networks”, IEEE Internet of Things Journal (IoT-J), Volume 3, Issue 4, pp. 464-479, Aug. 2016. DOI
  44. Zhongwei Si, Hong Yu, and Zhanyu Ma*,“Learning Deep Features for DNA Methylation Data Analysis”, IEEE ACCESS, vol. 4, pp. 2732 – 2737, June 2016. DOI
  45. Chunyun Zhang, Zhongwei Si, Zhanyu Ma*, Xiaoming Xi, Yilong Yin, “Mining Sequential Update Summarization with Hierarchical Text Analysis”, Mobile Information Systems, vol. 2016, Article ID 1340973, 10 pages, 2016. DOI
  46. Zhanyu Ma*, Zheng-Hua Tan, and Jun Guo, “Feature Selection for Neutral Vector in EEG Signal Classification”, NEUROCOMPUTING, vol. 174, pp. 937-945, Jan. 2016. DOI
  47. Mikael Davis*, Zhanyu Ma*, Weiru Liu, Paul Miller, Ruth Hunter, Frank Kee, “Generating realistic labelled, weighted random graphs”, Algorithms, 8(4), 1143-1174, 2015.DOI
  48. Zhanyu Ma*, Jalil Taghia, W. Bastiaan Kleijn, Arne Leijon, and Jun Guo, “Line Spectral Frequencies Modeling by a Mixture of Von Mises-Fisher Distributions”, Signal Processing (SP), vol. 114, 219-224, Sep. 2015. DOI
  49. Chunyun Zhang, Yichang Zhang, Weiran Xu*, Zhanyu Ma, Yan Leng, and Jun Guo, “Mining activation force defined dependency patterns for relation extraction”, Knowledge-Based Systems(KBS), vol. 86, pp. 278–287, Sep. 2015DOI
  50. Chunyun Zhang*, Weiran Xu, Zhanyu Ma, Sheng Gao, Qun Li, and Jun Guo, “Construction of Semantic Bootstrapping Models for Relation Extraction”, Knowledge-Based Systems(KBS), 83, 128-137, July 2015. DOI
  51. Kaili Zhao*, Honggang Zhang, Zhanyu Ma, Yi-Zhe Song, Jun Guo, “Multi-label learning with prior knowledge for facial expression analysis”, Neurocomputing, vol 157, pp. 280-289, June 2015. DOI
  52. Zhanyu Ma*, Andrew E. Teschendorff, Arne Leijon, Yuanyuan Qiao, Honggang Zhang, and Jun Guo, “Variational Bayesian Matrix Factorization for Bounded Support Data”, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), Volume 37, Issue 4, pp. 876 – 889, Apr. 2015. DOI (北京青年优秀科技论文一等奖,ESI高被引)
  53. Pravin K. Rana*, Jalil Taghia, Zhanyu Ma, and Markus Flierl, “Probabilistic Multiview Depth Image Enhancement Using Variational Inference”, IEEE Journal of Selected Topics in Signal Processing (J-STSP), Vol. 9, No. 3, pp. 435 – 448, April 2015. DOI
  54. Yuanyuan Qiao*, Jie Yang, Haiyang He, Yihang Cheng, and Zhanyu Ma, “User location prediction with energy efficiency model in the Long Term-Evolution network”, International Journal of Communicatino Systems (IJCS), Jan. 2015.
  55. Zhanyu Ma, Hailong Li, Qie Sun*, Chao Wang, Aibin Yan, and Fredrik Starfel,  “Statistical analysis of energy consumption patterns on the heat demand of buildings in district heating systems”, Energy and Buildings(ENB), pp. 464–472, Volume 85, December 2014. DOI
  56. Zhanyu Ma*, Saikat Chatterjee, W. Bastiaan Kleijn, and JunGuo, “Dirichlet Mixture Modeling to Estimate an Empirical Lower Bound for LSF Quantization”, Signal Processing (SP), Volume 104, pp. 291-295, November 2014. DOI
  57. Zhanyu Ma*, Pravin K. Rana, Jalil Taghia, Markus Flierl, and Arne Leijon, “Bayesian Estimation of Dirichlet Mixture Model with Variational Inference”, Pattern Recognition (PR), Volume 47, Issue 9, pp. 3143-3157, September 2014. DOI
  58. Jalil Taghia*, Zhanyu Ma, and Arne Leijon, “Bayesian Estimation of the von-Mises Fisher Mixture Model with Variational Inference”, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), Volume:36, Issue9, pp. 1701-1715, September, 2014. DOI
  59. Zhanyu Ma*, Andrew E. Teschendorff, Hong Yu, Jalil Taghia, and Jun Guo, “Comparisons of Non-Gaussian Statistical Models in DNA Methylation Analysis”, International Journal of Molecular Sciences (IJMS), 15(6), 10835-10854, 2014. DOI
  60. Zhanyu Ma*, Arne Leijon, Zheng-Hua Tan, and Sheng Gao, “Predictive Distribution of the Dirichlet Mixture Model by Local Variational Inference”, Journal of Signal Processing System (JSPS), Volume 74, Issue 3, pp.359-374, 2014. DOI
  61. Sheng Gao, Hao Luo, Da Chen, Shantao Li, Patrick. Gallinari, Zhanyu Ma, Jun Guo, “A Cross-Domain Recommendation Model for Cyber-Physical Systems”, IEEE Transactions on Emerging Topics in Computing, vol. 1, no. 2, pp. 384-393, Dec. 2014. DOI
  62. Zhanyu Ma*, Arne Leijon, and W. Bastiaan Kleijn, “Vector Quantization of LSF Parameters with a Mixture of Dirichlet Distributions”, IEEE Trans. on Audio, Speech, and Language Processing (TASLP), vol.21, no.9, pp.1777-1790, Sept. 2013. DOI
  63. Zhanyu Ma and Andrew E. Teschendorff*, “A Variational Bayes Beta Mixture Model for Feature Selection in DNA Methylation Studies”, Journal of Bioinformatics and Computational Biology (JBCB), Vol. 11, No. 4 (2013) 1350005 (19 pages), 2013. DOI
  64. Zhanyu Ma*, Arne Leijon, “Bayesian Estimation of Beta Mixture Models with Variational Inference”, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), Vol. 33, pp. 2160 – 2173, Nov. 2011. DOI

Conference papers (*=Corresponding author)

  1. Yifeng Ding, Shuwei Dong, Yujun Tong, Zhanyu Ma, Bo Xiao*, Haibin Ling, ” Channel DropBlock: An Improved Regularization Method for Fine-Grained Visual Classification”, in Proceedings of British Machine Vision Conference (BMVC), 2021. Code
  2. Yihui Shi, Yun Liu, Fangxiang Feng, Ruifan Li*, Zhanyu Ma, and Xiaojie Wang, “S2TD: A Tree-Structured Decoder for Image Paragraph Captioning”, in Proceedings of ACM Multimedia Asia Conference, 2021.
  3. Chenyu Guo, Jiyang Xie, Kongming Liang, Xian Sun, and Zhanyu Ma*, “Cross-layer Navigation Convolutional Neural Network for Fine-grained Visual Classification”, in Proceedings of ACM Multimedia Asia Conference, 2021. Code
  4. Zhen Yang, Zhou Ming, Haiyang Yu, Yingxu Lai, and Zhanyu Ma, “Privacy-Preserving Verifiable Collaborative Learning with Chain Aggregation”, in Proceedings of IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC), 2020.
  5. Jingye Wang, Yixiao Zheng, Weiyu Xiong, Junhan Chen, Zhanyu Ma*, and Rongliang Ma, “A Probabilistic Expression System for Fingerprint Identification Findings Based on Stability”, in Proceedings of IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC), 2020.
  6. Weiyu Xiong, Zhanyu Ma*, and Yi-Zhe Song, “Robust Augmentations for Small Object Detection of Aerial Images”, in Proceedings of IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC), 2020.
  7. Yazhou Li, Yihui Shi, Yun Liu, Ruifan Li, and Zhanyu Ma, “Image Captioning Based on An Improved Transformer with IoU Position Encoding”,  in Proceedings of Asia Pacific Signal and Information Processing Association (APSIPA), 2021.
  8. Zeyuan Wang, Zhiyu Wei, Lihui Zhang, Ruifan Li, and Zhanyu Ma, “Entailment Method Based on Template Selection for Chinese Text Few-Shot Learning”, in Proceedings of Asia Pacific Signal and Information Processing Association (APSIPA), 2021.
  9. Tian Zhang, Dongliang Chang, Zhanyu Ma*, and Jun Guo, “Progressive Co-attention Network for Fine-grained Visual Classification”, in Proceedings of IEEE International Conference on Visual Communications and Image Processing (VCIP), 2021. DOI Code
  10. Yurong Guo, Zhanyu Ma*, Xiaoxu Li, and Yuan Dong, “TLRM: Task-level Relation Module for GNN-based Few-Shot Learning”, in Proceedings of IEEE International Conference on Visual Communications and Image Processing (VCIP), 2021. DOI Code
  11. Shuai Xu, Dongliang Chang, Jiyang Xie, and Zhanyu Ma*, “Grad-Cam Guided Channel-Spatial Attention Module for Fine-Grained Visual Classification”, in Proceedings of IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2021. Code
  12. Haoyu Wang, Dongliang Chang, Weidong Liu, Bo Xiao*, Zhanyu Ma, Jun Guo, and Yaning Chang, “Exploring Category-shared and Category-specific Features for Fine-Grained Image Classification“, in Proceedings of Chinese Conference on Pattern Recognition and Computer Vision (PRCV), 2021.
  13. Jianhua Yang, Yan Huang, Zhanyu Ma, and Liang Wang, “CMF: Cascaded Multi-Model Fusion for Referring Image Segmentation”, in Proceedings of IEEE International Conference on Image Processing (ICIP), 2021.
  14. Wenyu Sun, Jiyang Xie, Jiayan Qiu, and Zhanyu Ma*, “Part Uncertainty Estimation Convolutional Neural Network for Person Re-Identification”, in Proceedings of IEEE International Conference on Image Processing (ICIP), 2021.
  15. Ruifan Li, Hao Chen, Fangxiang Feng, Zhanyu Ma, Xiaojie Wang, and Eduard Hovy, “Dual Graph Convolutional Networks for Aspect-based Sentiment Analysis”, in Proceedings of ACL-IJCNLP, 2021. Code
  16. Dongliang Chang, Kaiyue Pang, Yixiao Zheng, Zhanyu Ma*, Yi-Zhe Song, and Jun Guo, “Your “Flamingo” is My “Bird”: Fine-Grained, or Not”, in Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognitions (CVPR), Oral, 2021. DOI Code
  17. Siqing Zhang, Ruoyi Du, Dongliang Chang, Zhanyu Ma*, Jun Guo, “Knowledge Transfer Based Fine-Grained Visual Classification”, in Proceedings of
    IEEE International Conference on Multimedia and Expo (ICME), 2021. Code
  18. Yiming Zhang, Hong Yu, and Zhanyu Ma, “Speaker Verification System Based on Deformable CNN and Time-Frequency Attention”, in Proceedings of Asia Pacific Signal and Information Processing Association (APSIPA), 2020.
  19. Xiaoxu Li, Tao Tian, Yuxin Liu, Hong Yu*, Jie Cao, and Zhanyu Ma*, “Adaptive Multi-prototype Relation Network”, in Proceedings of Asia Pacific Signal and Information Processing Association (APSIPA), 2020.
  20. Xiaoxu Li, Jintao Yan, Jijie Wu, Yuxin Liu, Xiaochen Yang*, and Zhanyu Ma*, “Anti-Noise Relation Network for Few-shot learning”, in Proceedings of Asia Pacific Signal and Information Processing Association (APSIPA), 2020.
  21. Jianhua Yang, Yan Huang, Linjiang Huang, Yunbo Wang, Zhanyu Ma, and Liang Wang, “Global Context Enhanced Multi-modal Fusion for Referring Image Segmentation”, in Proceedings of Chinese Conference on Pattern Recognition and Computer Vision (PRCV), 2020.
  22. Ruoyi Du, Dongliang Chang, Ayan Kumar Bhunia, Jiyang Xie, Zhanyu Ma*, Yi-Zhe Song, and Jun Guo, “Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches”, in Proceedings of European Conference on Computer Vision (ECCV), 2020. Arxiv Code
  23. Tianyi Wu, Yu Lu, Yu Zhu, Chuang Zhang*, Ming Wu, Zhanyu Ma, and Guodong Guo, “GINet: Graph Interaction Network for Scene Parsing”, in Proceedings of European Conference on Computer Vision (ECCV), 2020.
  24. Junhui Yin, Siqing Zhang, Dongliang Chang, Zhanyu Ma*, and Jun Guo, “Dual-attention Guided Dropblock Module for Weakly Supervised Object Localization”, in Proceedings of International Conference on Pattern Recognition (ICPR), 2020.
  25. Zeyu Song, Dongliang Chang, Zhanyu Ma*, Xiaoxu Li, and Zheng-Hua Tan, “CC-Loss: Channel Correlation Loss For Image Classification”, in Proceedings of International Conference on Pattern Recognition (ICPR), 2020.
  26. Yixiao Zheng, Dongliang Chang, Jiyang Xie, and Zhanyu Ma*, “IU-Module: Intersection and Union Module for Fine-Grained Visual Classification”, in Proceedings of IEEE International Conference on Multimedia and Expo (ICME), 2020.
  27. Xinran Wei, Dongliang Chang, Jiyang Xie, Yixiao Zheng, Chen Gong, and Zhanyu Ma*, “FICAL: Focal Inter-Class Angular Loss for Image Classification”, in Proceedings of IEEE International Conference on Visual Communications and Image Processing (VCIP), 2019.
  28. Ke Zhang, Xinsheng Wang, Yurong Guo, Zhenbing Zhao, and Zhanyu Ma, “Competing Ratio Loss for Multi-class image Classification”, in Proceedings of IEEE International Conference on Visual Communications and Image Processing (VCIP), 2019.
  29. Xiaoxu Li, Liyun Yu, Dongliang Chang, Zhanyu Ma*, and Jie Cao, “Small-Sample Image Classification Method of Combining Prototype and Margin Learning”, in Proceedings of Asia Pacific Signal and Information Processing Association (APSIPA), 2019.
  30. Xiaoxu Li, Jijie Wu, Dongliang Chang, Zhanyu Ma*, and Jie Cao, “Mixed Attention Mechanism for Small-Sample Fine-grained Image Classification”, in Proceedings of Asia Pacific Signal and Information Processing Association (APSIPA), 2019.
  31. Jie Cao, Yaofeng Zhou, Hong Yu, Xiaoxu Li*, and Zhanyu Ma,” A Loss With Mixed Penalty for Speech Enhancement Generative Adversarial Network”, in Proceedings of Asia Pacific Signal and Information Processing Association(APSIPA), 2019.
  32. Jie Cao, Yinping Qiu, Dongliang Chang, Xiaoxu Li*, and Zhanyu Ma,” Dynamic Attention Loss for Small-Sample Image Classification”, in Proceedings of Asia Pacific Signal and Information Processing Association(APSIPA), 2019.
  33. Lu Cheng, Dongliang Chang*, Jiyang Xie, Rongliang Ma, Chunsheng Wu, and Zhanyu Ma, “Channel Max Pooling for Image Classification”, in Proceedings of International Conference on Intelligence Science and Big Data Engineering (IScIDE), 2019.
  34. Jiyang Xie, Zhanyu Ma*, Guoqiang Zhang, Jing-Hao Xue, Zheng-Hua Tan, and Jun Guo, “Soft Dropout and Its Variational Bayes Approximation”, in Proceedings of IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2019.
  35. Ke Zhang, Yurong Guo, Xinsheng Wang, Jinsha Yuan, Zhanyu Ma, and Zhenbing Zhao, “Channel-wise and Feature-Points Reweights DenseNet For Image Classification”, in Proceedings of IEEE International Conference on Image Processing (ICIP), 2019.
  36. Yao Xie, Peng Xu, and Zhanyu Ma*, “Deep Zero-Shot Learning for Scene Sketch”, in Proceedings of IEEE International Conference on Image Processing (ICIP), 2019.
  37. Jiyang Xie, Zhanyu Ma*, Guoqiang Zhang, Jing-Hao Xue, Jen-Tzung Chien, Zhiqing Lin, and Jun Guo, “BALSON: BAYESIAN LEAST SQUARES OPTIMIZATION WITH NONNEGATIVE L1-NORM CONSTRAINT”, in Proceedings of IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2018.
  38. Hong Yu, Tianrui Hu, Zhanyu Ma*, Zheng-Hua Tan, and Jun Guo, “Multi-Task Adversarial Network Bottleneck Features for Noise-Robust Speaker Verification”, in Proceedings of IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC), 2018.
  39. Jiyang Xie, Jiaxin Guo, Zhanyu Ma*, Jing-Hao Xue, Qie Sun, Hailong Li, and Jun Guo, “SEA: A Combined Model for Heat Demand Prediction”, in Proceedings of IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC), 2018.
  40. Xinran Wei, Jiyang Xie, Wenrui He, Min Min, Zhanyu Ma*, and Jun Guo, “Quantitative Comparisons of Linked Color Imaging and White-Light Colonoscopy for Colorectal Polyp Analysis”, in Proceedings of IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC), 2018.
  41. Peng Xu, Yongye Huang, Tongtong Yuan, Kaiyue Pang, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales, Zhanyu Ma*, and Jun Guo, “SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval”, in Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognitions (CVPR), 2018.
  42. Y. Li, J. Zhang, and Z. Ma, “Clustering in Wireless Propagation Channel with a Statistics-based Framework”, in Proceedings of IEEE Wireless Communications and Networking Conference (WCNC), Apr. 15-18, 2018.
  43. Z. Liu, Y. Qi, Z. Ma, and J. Yang, “Sentiment Analysis by Exploring Large Scale Web-based Chinese Short Text”, in Proceedings of The International Conference on Computer Science and Application Engineering (CSAE), Oct. 21-23, 2017.
  44. F. Zhu, X. Li, Z. Ma*, G. Chen, P. Peng, X. Guo, J.-T. Chien, and J. Guo, “Image-text Dual Model for Small-sample Image Classication”, in Proceedings of Chinese Conference on Computer Vision (CCCV) 2017, Oct. 11-14, 2017.
  45. H. Yu, Z.-H. Tan, Z. Ma*, and J. Guo, “Adversarial Network Bottleneck Features for Noise Robust Speaker Verification”, INTERSPEECH, 2017. arXiv: 1706.03397
  46. X. Ma, J. Zhang, Y. Zhang, Z. Ma, and Y. Zhang, “A PCA-based Modeling Method for Wireless MIMO Channel”, INFOCOM, 2017.
  47. J. Xie, H. Li*, Z. Ma*, Q. Sun*, F. Wallin, Z. Si, and J. Guo, “Analysis of Key Factors in Heat Demand Prediction with Neural Networks”, in Proceedings of International Conference on Applied Energy (ICAE), Oct. 8-11, 2016.
  48. P. Xu, Q. Yin, Y. Qi,  Y.-Z. Song, Z. Ma*, L. Wang, J. Guo, “Instance-level Coupled Subspace Learning for Fine-grained Sketch-based Image Retrieval”, in Proceedings of European Conference on Computer Vision Workshop, Oct. 8-16, 2016.
  49. P. Xu, K. Li, Z. Ma*, Y.-Z. Song, L. Wang, J. Guo, “Cross-modal Subspace Learning for Sketch-based Image Retrieval: A Comparative Study”, in Proceedings of IEEE International Conference on Network Infrastructure and Digital Content, Sept. 23-25, 2016. (Best Paper Award)
  50. H. Zhou, N. Zhang, D. Huang, Z. Ma*, W. Hu, and J. Guo, “Activation Force-based Air Pollution Tracing”, in Proceedings of IEEE International Conference on Network Infrastructure and Digital Content, Sept. 23-25, 2016.
  51. Z. Wang*, Y. Qi, J. Liu, and Z. Ma, “User Intention Understanding From Scratch”, IEEE International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE), 6-8 July, 2016.
  52. Y. Chen, Y. Li, F. Qi, Z. Ma, H. Zhang, “Cycled Merging Registration of Point Clouds for 3D Human Body Modeling”, IEEE International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE), 6-8 July, 2016.
  53. H. Yu, A. Sarkar, D. A. L. Thomsen, Z.-H. Tan , Z. Ma , and J. Guo, “Effect of Multi-condition Training and Speech Enhancement Methods on Spoofing Detection”, IEEE International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE), 6-8 July, 2016.
  54. Y. Sun, W. Wang, H. Zhang, Z. Ma, “Detecting Formula based on Stroke Width Transform for online Chinese Examination Question Retrieval”, IEEE Digital Media Industry and Academic Forum, 4-6 July, 2016.
  55. L. Qi, Y. Qiao, F. B. Abdesslem, Z. Ma, J. Yang, “Oscillation Resolution for Massive Cell Phone Traffic Data”, ACM MobiSys Workshop on Mobile Data, 30 June, 2016.
  56. V. Nian, Q. Sun, Z. Ma, and H. Li. “A comparative cost assessment of energy production from central heating plant or power plant waste heat recovery “, CUE2016-Applied Energy Symposium and Forum, June 13-15, 2016.
  57. D. Huang, N. Zhang, H. Yu, H. Zhou, Z. Ma*, W. Hu, and J. Guo, “Activation Force-based Air Pollution Observation Station Clustering”, QSHINE, 19-20 August, Taipei, 2015.
  58. C. Zhang, Z. Ma*, J. Zhang, W. Xu, and J. Guo, “A Multi-level System for Sequential Update Summarization”, QSHINE, 19-20 August, Taipei, 2015.
  59. R. L. Kristensen*, Z.-H. Tan, Z. Ma, and J. Guo, “Binary Pattern Flavored Feature Extractors for Facial Expression Recognition: An Overview,” CIS-MIPRO 2015, 25-29 May 2015, Opatija, Croatia.
  60. H. Yu*, Z. Ma, M. Li, and J. Guo, “Histogram Transform Model Uding MFCC Features for Text-independent Speaker Identification”, in Proceedings of IEEE Asilomar Conference on Signals, Systems, and Computers (Asilomar SS&C), November 2014.
  61. F. Qi*, H. Zhang, Z. Ma, and N. Liu, “Supervoxel for Human and Clothes in RGB-D Image”, in Proceedings of Global Wireless Summit (GWS), 2014.
  62. Z. Ma*, R. Martin, J. Guo, and H. Zhang, “Nonlinear estimation of missing ΔLSF parameters by a mixture of Dirichlet distributions”, in Proceedings of International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2014.
  63. Z. Ma*, Q. Sun, H. Li, C. Wang, A. Yan, and F. Starfelt, “Dynamic Prediction of the Heat Demand for Buildings in District Heating Systems”, in Proceedings of International Conference on Applied Energy (ICAE), 2013.
  64. P. K. Rana, Z. Ma, J. Taghia, and M. Flierl, “Multiview Depth Map Enhancement by Variational Bayes Inference Estimation of Dirichlet Mixture Models”, in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 1528–1532, May 2013.
  65. J.Taghia, Z. Ma, and A. Leijon, “On Von-Mises Fisher Mixture Model in Text-Independent Speaker Identification”, in Proceedings of INTERSPEECH, 2013.
  66. Z. Ma* “Bayesian Estimation of the Dirichlet Distribution with Expectation Propagation”, in Proceedings of European Signal Processing Conference (EUSIPCO), pp. 689-693, 2012.
  67. Z. Ma* Z. –H. Tan, and S. Prasad, “EEG Signal Classification with Super-Dirichlet Mixture Model”, in Proceedings of IEEE Statistical Signal Processing Workshop (SSP), pp. 440-443, 2012.
  68. Z. Ma* and A. Leijon, “A Model-based Collaborative Filtering Method for Bounded Support Data”, in proceedings of IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC), 2012.
  69. Z. Ma* and A. Leijon, “Approximating the Predictive Distribution of the Beta Distribution with the Local Variational Method”, in Proceedings of IEEE International Workshop on Machine Learning for Signal Processing (MLSP), pp. 1-6, 2011.
  70. Z. Ma* and A. Leijon, “Super-Dirichlet Mixture Models using Differential Line Spectral Frequencies for Text-Independent Speaker Identification”, in Proceedings of INTERSPEECH, pp. 2349-2352, 2011.
  71. Z. Ma* and A. Leijon, “Expectation Propagation for Estimating the Parameters of the Beta Distribution”, in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 2082-2085, 2010.
  72. Z. Ma* and A. Leijon, “Modeling Speech Line Spectral Frequencies with Dirichlet Mixture Models”, in Proceedings of INTERSPEECH, pp. 2370-2373, 2010.
  73. Z. Ma* and A. Leijon, “PDF-optimized LSF Vector Quantization Based on Beta Mixture Models”, in Proceedings of INTERSPEECH, pp. 2374-2377, 2010.
  74. Z. Ma* and A. Leijon, “Human Skin Color Detection in RGB Space with Bayesian Estimation of Beta Mixture Models”, in Proceedings of European Signal Processing Conference (EUSIPCO), pp. 1204-1208, 2010.
  75. Z. Ma* and A. Leijon, “Coding Bounded Support Data with Beta Distribution”, in Proceedings of IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC), pp. 246-250, 2010.
  76. Z. Ma* and A. Leijon, “Beta Mixture Models and the Application to Image Classification”, in Proceedings of IEEE International Conference on Image Processing (ICIP), pp. 2045-2048, 2009.
  77. Z. Ma* and A. Leijon, “Human Audio-Visual Consonant Recognition Analyzed with Three Bimodal Integration Models”, in Proceedings of INTERSPEECH, pp. 812-815, 2009.
  78. Z. Ma* and A. Leijon, “A Probabilistic Principal Component Analysis Based Hidden Markov Model for Audio-Visual Speech Recognition”, in Proceedings of IEEE Asilomar Conference on Signals, Systems, and Computers (Asilomar SS&C), pp. 2170-2173, 2008.