个人简历

马占宇，北京邮电大学教授、博士生导师；瑞典皇家理工学院（KTH-Royal Institute of Technology）博士、博士后；IEEE高级会员，中国图象图形学学会高级会员、理事、副秘书长、青年工作委员会副主任，中国计算机学会高级会员、计算机视觉专委会秘书长、会员与分部工作委员会执行委员。共在包括IEEE TPAMI在内的期刊和会议上发表论文100多篇，担任IEEE Transactions on Vehicular Techonology，IEEE ACCESS，NEUROCOMPUTING ，中国邮电高校学报（英文版）等期刊的编委，担任SPLINE 2016 Technical Co-Chair，IEEE MLSP 2018 Program Chair等国际会议职务或委员；主持国家自然科学基金“优秀青年科学基金”、国家自然科学基金”企业联合创新重点基金“，科技部重点研发计划课题等项目；曾获中国人工智能学会“第七届吴文俊人工智能科学技术奖”一等奖，“北京市科学技术奖”二等奖，“北京青年优秀科技论文”一等奖；入选北京智源人工智能研究院“智源青年科学家”，”北京市科技新星”计划等。

研究领域

主要研究方向是以数据的非高斯建模与分析为代表的模式识别与机器学习基础理论与方法，及其在计算机视觉、城市大数据分析、多媒体信号处理等领域的应用。

近期论文

Zhanyu Ma, “Non-Gaussian Statistical Models and Their Applications”, PhD Thesis, KTH-Royal Institute of Technology, Stockholm, Sweden, 2011. Link
期刊 (*=通信作者)
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), accepted. DOI Code
Xiaoxu Li, Dongliang Chang, Zhanyu Ma*,Zheng-Hua Tan, Jing-Hao
Xue, Jie Cao, and Jun Guo, “Deep InterBoost Networks for Small-sample Image Classication”, NEUROCOMPUTING, accepted.
Xiaoxu Li, Zhuo Sun, Jing-Hao Xue*, and Zhanyu Ma, “A Concise Review of Recent Few-shot Meta-learning Methods”, NEUROCOMPUTING, accepted.
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
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). DOI
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), accepted. DOI
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), accepted. DOI
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
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
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
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
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
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
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
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 (ESI高被引)
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
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. DOI （ESI热点、高被引）
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. DOI（ESI高被引）
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. DOI （ESI热点、高被引）
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
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
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
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
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
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
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. DOI （ESI热点、高被引）
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
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
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
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
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
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
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
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
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
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
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. 2015. DOI
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
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
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)
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
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.
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
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
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
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
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
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
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
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
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
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 (被Nature引用)
会议 (*=通信作者)
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.
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. DOI Code
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 Conference on Computer Vision and Pattern Recognitions (CVPR), 2018.
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.
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.
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, Oral (18%), Oct. 11-14, 2017.
H. Yu, Z.-H. Tan, Z. Ma*, and J. Guo, “Adversarial Network Bottleneck Features for Noise Robust Speaker Verification”, INTERSPEECH, 2017. arXiv: 1706.03397
X. Ma, J. Zhang, Y. Zhang, Z. Ma and Y. Zhang, “A PCA-based Modeling Method for Wireless MIMO Channel”, INFOCOM, 874 – 879,2017.
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.
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.
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 (IC-NIDC), Sept. 23-25, 2016. (Best paper award)
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.
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.
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.
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.
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.
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.
V. Nian, Q. Sun, and 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.
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.
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.
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.
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.
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.
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.
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.
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.
J.Taghia, Z. Ma, and A. Leijon, “On Von-Mises Fisher Mixture Model in Text-Independent Speaker Identification”, in Proceedings of INTERSPEECH, 2013.
Z. Ma* “Bayesian Estimation of the Dirichlet Distribution with Expectation Propagation”, in Proceedings of European Signal Processing Conference (EUSIPCO), pp. 689-693, 2012.
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.
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.
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.
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.
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.
Z. Ma* and A. Leijon, “Modeling Speech Line Spectral Frequencies with Dirichlet Mixture Models”, in Proceedings of INTERSPEECH, pp. 2370-2373, 2010.
Z. Ma* and A. Leijon, “PDF-optimized LSF Vector Quantization Based on Beta Mixture Models”, in Proceedings of INTERSPEECH, pp. 2374-2377, 2010.
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.
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.
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.
Z. Ma* and A. Leijon, “Human Audio-Visual Consonant Recognition Analyzed with Three Bimodal Integration Models”, in Proceedings of INTERSPEECH, pp. 812-815, 2009.
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.