唐厂

基本信息Personal Information

博士生导师 硕士生导师

性别 : 男

毕业院校 : 天津大学

学历 : 博士研究生

学位 : 博士

在职信息 : 在职

所在单位 : 计算机学院

入职时间 : 2017年03月01日

扫描关注

个人简介Personal Profile

唐厂,男,中共党员,中国地质大学(武汉)计算机学院教授,博士生导师,湖北省省级人才。2016年博士毕业于天津大学电子信息工程学院信息与通信工程专业。曾于2014年9月至2015年9月在澳大利亚University of Wollongong计算机科学与技术学院交流学习一年。IEEE/ACM/CCF/CSIAM会员,CAAI终身会员,CCF理论计算机科学专委(CCF-NCTCS)委员,CCF人工智能与模式识别专业委员会(CCF-AI)执行委员,中国人工智能学会机器学习专业委员会委员,中国工业与应用数学学会(CSIAM )大数据与人工智能专业委员会委员,全国高校大数据教育联盟专委委员, SCI期刊BioMed Research International和BMC Bioinformatics的Associate Editor。中国人工智能学会会刊《CAAI Transactions on Intelligence Technology》及《计算机工程》青年编委。主要研究方向包括:机器学习和计算机视觉。近5年以来主持国家自然科学基金青年基金项目一项,国家自然科学基金面上项目一项,中国人工智能学会-华为Mindspore创新基金一项,湖北省面上项目一项,实验室开放基金若干项以及“地大学者”青年优秀人才项目一项,入选2019年武汉市青年科技朝阳计划。发表SCI检索期刊学术论文和CCF A类会议论文总计60余篇, ESI高被引论文5篇,ESI热点论文1篇。谷歌学术总引3300余次。指导硕士研究生获第五届亚洲人工智能会议(ACAIT 2021)最佳论文奖。此外,还担任IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI),IEEE Transactions on Image Processing (IEEE TIP), IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS),IEEE Transactions on Multimedia(IEEE TMM),IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT),IEEE Transactions on Cybernetics(IEEE TCyB), IEEE Transactions on Network Science and Engineering (IEEE TNSE),IEEE Transactions on Biomedical Engineering (IEEE TBE),IEEE Transactions on Big Data (IEEE TBD),IEEE Computational Intelligence Magazine (IEEE CIM),IEEE Transactions on Emerging Topics in Computational Intelligence (IEEE TETCI),中国科学:信息科学 等重要期刊的审稿人。长期担任CCF A/B类重要会议CVPR、ICML、ICCV、NIPS、IJCAI、AAAI、ECCV、ICME等的程序委员会委员或领域主席。


---------目前从事机器学习、深度学习、计算机视觉、遥感影像解译、医学影像分析、生物医学数据处理、计算生物学等相关方面的研究,欢迎对科研有兴趣和热情的同学邮件联系我(要求数学、编程和英语基础较好)。

---------来信前请务必点击链接阅读招生政策:来信前必读,为及时回复同学们的邮件,请同学们务必在邮件中注明“已阅读《来信前必读》”。

联系方式:tangchang##cug.edu.cn(将##替换成@)

详细信息请见:http://tangchang.net


科研项目(主持):

  1. 1. 复杂多视图数据的表征学习及聚类算法研究,国家自然科学基金面上项目,2021-01-01--2024-12-31

  2. 2. 基于深度学习的高光谱智能目标识别方法研究,山东省自然科学基金创新发展联合基金,2022-01-01--2024-12-31

  3. 3. 基于图模型的图像显著性目标检测理论与方法研究,国家自然科学基金青年项目,2018-01-01--2020-12-31

  4. 4. 深度神经网络中的层级特征融合关键技术与方法,中国人工智能学会(CAAI)-华为MindSpore创新基金,2020-12-01--2021-11-30

  5. 5. 复杂多视图数据的聚类理论与方法研究,湖北省自然科学基金面上项目,2020-03-01--2022-03-31

  6. 6. miRNA和复杂疾病的关联预测计算方法研究,深圳大学实验室开放基金,2019-10-20--2021-10-20

  7. 7. 多视图数据的聚类理论与方法,南京大学计算机软件新技术国家重点实验室开放基金,2021-07-01--2023-06-30


毕业生去向:

研究生:

田婓 (2022年6月毕业):华为(深圳)(2022年优秀硕士论文

万诚(2020年6月毕业):招商银行(深圳)

李正来(2021年6月毕业): 继续攻读博士学位(中国地质大学(武汉))

本科生:

何潇 (2022年6月毕业):升学至中国地质大学(武汉)计算机学院学术硕士

李计成 (2022年6月毕业):升学至中国地质大学(武汉)计算机学院学术硕士

陈兴瑞 (2022年6月毕业):字节跳动(北京)

刘夕源 (2022年6月毕业):升学至华中科技大学计算机学院 硕士

刘畅海 (2022年6月毕业):升学至日本 硕士

王朝伟(2022年6月毕业):升学至西北工业大学 硕士 (2022年优秀学士论文


薛锋靖阳(2021年6月毕业): 就读国外硕士,加拿大(McMaster University,麦克马斯特大学)

黄晓琳(2021年6月毕业):保研升学(厦门大学)

李帆(2020年6月毕业):考研升学(西北工业大学)



代表性论文如下(2018-今):

Pre-print


2023
undefinedChang Tang, Xiao Zheng, Zhiguo Wan, Chengyu Hu, Wei Zhang, "Multi-level Confidence Learning for Trustworthy Multimodal Classification", Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023.
2022
undefinedChang Tang, Xiao Zheng, Wei Zhang, Xinwang Liu, Xinzhong Zhu, En Zhu, "Unsupervised Feature Selection via Multiple Graph Fusion and Feature Weight Learning", SCIENCE CHINA Information Sciences, Accepted, 2022. [CODE]
undefinedWeiqing Yan, Jindong Xu, Jinglei Liu, Guanghui Yue, Chang Tang*, "Bipartite Graph-based Discriminative Feature Learning for Multi-View Clustering", ACM International Conference on Multimedia (ACM MM), 2022.
undefinedChang Tang, Zhenglai Li, Weiqing Yan, Guanghui Yue, Wei Zhang, "Efficient Multiple Kernel Clustering via Spectral Perturbation", ACM International Conference on Multimedia (ACM MM), 2022.
undefinedZhenglai Li, Chang Tang*, Lizhe Wang, Albert Zomaya. "Remote Sensing Change Detection via Temporal Feature Interaction and Guided Refinement", IEEE Transactions on Geoscience and Remote Sensing, 2022.[CODE]


undefinedChang Tang, Zhenglai Li, Jun Wang, Xinwang Liu, Wei Zhang, En Zhu, "Unified One-step Multi-view Spectral Clustering", IEEE Transactions on Knowledge and Data Engineering, Accepted, 2022. [CODE]


undefinedJun Wang, Chang Tang*, Xinwang Liu, Wei Zhang, Wanqing Li, Xinzhong Zhu, Lizhe Wang, Albert Zomaya. "Region-aware Hierarchical Latent Feature Representation Learning Guided Clustering for Hyperspectral Band Clustering", IEEE Transactions on Cybernetics, 2022. [CODE]


undefinedJun Wang, Chang Tang*, Xiao Zheng, Xinwang Liu, Wei Zhang, En Zhu. "Graph Regularized Spatial-spectral Subspace Clustering for Hyperspectral Band Selection", Neural Networks, 2022. [CODE]


undefinedZheng Li, Chang Tang*, Xiao Zheng, Zhenglai Li, Wei Zhang. "Unified K-means Coupled Self-representation and Neighborhood Kernel Learning for Clustering Single-cell RNA-Sequencing Data", Neurocomputing, 2022. 
Zhenglai Li, Chang Tang*, Xiao Zheng, Xinwang Liu, Wei Zhang, En Zhu, "High-order Correlation Preserved Incomplete Multi-view Subspace Clustering", IEEE Transactions on Image Processing, Accepted, 2022. [CODE]
唐厂, 王俊, "基于近邻子空间划分的高光谱影像波段选择方法", 天津大学学报(自然科学与工程技术版), 55(3), 255-262, 2022. [CODE]
2021


Jun Wang, Chang Tang*, Zhenglai Li, Xinwang Liu, Wei Zhang, En Zhu, Lizhe Wang, "Hyperspectral Band Selection via Region-aware Latent Features Fusion Based Clustering", Information Fusion (Accepted), 2021.
Tang Chang, Liu Xinwang, Zhang Wei, Wang Lizhe, Zomaya Albert, "Hyperspectral Band Selection via Spatial-Spectral Weighted Region-wise Multiple Graph Fusion-Based Spectral Clustering", IJCAI 2021.
Chang Tang, Xiao Zheng, Xinwang Liu, Wei Zhang, Jing Zhang, Jian Xiong, and Lizhe Wang, "Cross-view Locality Preserved Diversity and Consensus Learning for Multi-view Unsupervised Feature Selection", IEEE Transactions on Knowledge and Data Engineering (Accepted), 2021.
Zhenglai Li, Chang Tang*, Xinwang Liu, Xiao Zheng, Wei Zhang, En Zhu, "Consensus Graph Learning for Multi-view Clustering". IEEE Transactions on Multimedia (Accepted), 2021.

[Codes:BaiduYun][bib]

Zhenglai Li, Chang Tang*, Xinwang Liu, Xiao Zheng, Wei Zhang, En Zhu, "Tensor-based Multi-view Block-diagonal Structure Diffusion for Clustering Incomplete Multi-view Data", IEEE ICME, 2021.

[Codes:BaiduYun]

Hanyu Yang, Xutao Li, Wenhao Qiang, Yuhan Zhao, Wei Zhang*, Chang Tang*, "A network traffic forecasting method based on SA optimized ARIMA–BP neural network", Computer Networks, 193(108102), 2021.
2020


Chang Tang, Xinwang Liu, Xiao Zheng, Wanqing Li, Jian Xiong, Lizhe Wang, Albert Zomaya, Antonella Longo, "DeFusionNET: Defocus Blur Detection via Recurrently Fusing and Refining Discriminative Multi-scale Deep Features", IEEE Transactions on Pattern Analysis and Machine Intelligence (Accepted),

[Codes:BaiduYun][CTCUG Dataset: Baidu Yun (Extraction code:shyk)|Google Drive]|CTCUG_Results(Extraction code: kwpd)|CVPR2014_Results(Extraction code: b7i4)|DUT_Results(Extraction code: ui5e)

Chang Tang, Xinwang Liu, Shan An, Pichao Wang, "BR2Net: Defocus Blur Detection via Bidirectional Channel Attention Residual Refining Network", IEEE Transactions on Multimedia (Accepted),

[Codes:BaiduYun]

Chang Tang, Xinwang Liu, Xinzhong Zhu, En Zhu, Zhigang Luo, Lizhe Wang, Wen Gao, "CGD: Multi-view Clustering via Cross-view Graph Diffusion", AAAI Conference on Artificial Intelligence (AAAI), 2020. [Code]
Chang Tang, Xinwang Liu, Xinzhong Zhu, En Zhu, Kun Sun, Pichao Wang, Lizhe Wang, Albert Zomaya, "R2MRF: Defocus Blur Detection via Recurrently Refining Multi-scale Residual Features", AAAI Conference on Artificial Intelligence (AAAI), 2020.
Xinwang Liu, Miaomiao Li, Chang Tang, Jingyuan Xia, Jian Xiong, Li Liu, Marius Kloft, En Zhu, "Efficient and Effective Regularized Incomplete Multi-view Clustering",    IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020.

[DOI]

Miaomiao Li, Zhenglai Li, Chang Tang, Xinwang Liu, Lulu Wang, "Robust Multi-View Clustering With A Unified Weight Learning Paradigm",    IEEE Access, 1-9, 2020.

[DOI]

Weiqing Yan, Guanghui Yue, Yuming Fang, Hua Chen, Chang Tang, Gangyi Jiang, "Perceptual Objective Quality Assessment of Stereoscopic Stitched Images", Signal Processing, 2020.

[DOI]

WeiqingYan, Guanghui Yue, Jindong Xu, Yanwei Yu, Kai Wang, Chang Tang, Xiangrong Tong, "Shape-optimizing mesh warping method for stereoscopic panorama stitching", Information Sciences, 511, 58-73, 2020.

[DOI]

Deqiong Ding, Xiaogao Yang, Fei Xia, Tiefeng Ma, Haiyun Liu, Chang Tang, "Unsupervised feature selection via adaptive hypergraph regularized latent representation learning", Neurocomputing, 378, 79-97, 2020.
Deqiong Ding, Fei Xia, Xiaogao Yang, Chang Tang*, "Joint dictionary and graph learning for unsupervised feature selection", Applied Intelligence, DOI: https://doi.org/10.1007/s10489-019-01561-x, 2020. (通讯作者)
2019


Chang Tang, Meiru Bian, Xinwang Liu, Miaomiao Li, Hua Zhou, Pichao Wang, Hailin Yin, "Unsupervised Feature Selection via Latent Representation Learning and Manifold Regularization", Neural Networks, 117, 163-178, 2019.

[Codes:BaiduYun][bib]

Chang Tang, Xinwang Liu, Xinzhong Zhu, Jian Xiong, Miaomiao Li, Jingyuan Xia, Xiangke Wang, Lizhe Wang, "Feature Selective Projection with Low-Rank Embedding and Dual Laplacian Regularization", IEEE Transactions on Knowledge and Data Engineering, 32(9), 1747-1760, 2020. DOI

[Code][bib][DOI]

Chang Tang, Xinwang Liu, Pichao Wang, Changqing Zhang, Miaomiao Li, Lizhe Wang, "Adaptive Hypergraph Learning for Multi-label Image Annotation", IEEE Transactions on Multimedia, 21(11), 2837-2849, 2019.

[Code][bib][DOI]

Chang Tang, Xinwang Liu, Xinzhong Zhu, Pichao Wang, "Salient Object Detection via Recurrently Aggregating Spatial Attention Weighted Cross-level Deep Features", ICME, 1546-1551, 2019.

[Code][bib][pdf]

Chang Tang, Xinwang Liu, Xinzhong Zhu, Lizhe Wang, Albert Zomaya, "DeFusionNET: Defocus Blur Detection via Recurrently Fusing and Refining Multi-scale Deep Features", CVPR, 2700-2709, 2019.

[Code][bib][pdf][Results: Baidu Yun (Extraction code: sit2)|Google Drive]

Xinwang Liu, Xinzhong Zhu, Miaomiao Li, Lei Wang, Chang Tang, Jianping Yin, Dinggang Shen, Huaimin Wang, Wen Gao, "Late Fusion Incomplete Multi-view Clustering", IEEE Transactions on Pattern Analysis and Machine Intelligence (Accepted)

[Code][bib][pdf]

Chang Tang, Xinzhong Zhu, Xinwang Liu, Miaomiao Li, Pichao Wang, Changqing Zhang and Lizhe Wang, "Learning a Joint Affinity Graph for Multiview Subspace Clustering", IEEE Transactions on Multimedia, 21(7), 1724-1736, 2019.

[Code(Extraction Code: 649k)][bib][DOI]



Chang Tang, Xinzhong Zhu, Xinwang Liu, Lizhe Wang, "Cross-view Local Structure Preserved Diversity and Consensus Learning for Multi-view Unsupervised Feature Selection", AAAI, 5101-5108, 2019.

[pdf]

Xinwang Liu, Xinzhong Zhu, Miaomiao Li, Chang Tang, En Zhu, Jianping Yin, Wen Gao, "Efficient and Effective Incomplete Multi-view Clustering", AAAI, 2019.

[pdf]

Siwei Wang, Xinwang Liu, En Zhu, Chang Tang, Jiyuan Liu, Jingtao Hu, Jingyuan Xia, Jianping Yin, "Multi-view Clustering via Late Fusion Alignment Maximization", IJCAI, 3778-3784, 2019.

[pdf]

Yawei Zhao, En Zhu, Xinwang Liu, Chang Tang, Deke Guo, Jianping Yin, "Simultaneous Clustering and Optimization for Evolving Datasets", IEEE Transactions on Knowledge and Data Engineering, 2019.

[DOI]

Zhenglai Li, Chang Tang, Jiajia Chen, Cheng Wan, Weiqing Yan, Xinwang Liu, "Diversity and consistency learning guided spectral embedding for multi-view clustering", Neurocomputing, 370, 128-139, 2019.

[DOI]

Shaoyong Li, Chang Tang, Xinwang Liu, Yaping Liu, Jiajia Chen, "Dual graph regularized compact feature representation for unsupervised feature selection", Neurocomputing, 331, 77-96, 2019.

[DOI]

2018


Chang Tang, Wanqing Li, Pichao Wang, Lizhe Wang "Online Action Recognition Based on Incremental Learning of Weighted Covariance Descriptors", Information Sciences, 467, 219-237 , 2018.

[Data set][Code(Coming soon!)][bibLink]

Chang Tang, Jiajia Chen, Xinwang Liu, Miaomiao Li, Pichao Wang, Minhui Wang, Peng Lu, "Consensus Learning Guided Multi-view Unsupervised Feature Selection", Knowledge-Based Systems, 160, 49-60, 2018.

[Code((Extraction code: qqb3))][bibLink]

Xinzhong Zhu*, Chang Tang*, Pichao Wang, Huiying Xu, Minhui Wang, Jie Tian, "Saliency Detection via Affinity Graph Learning and Weighted Manifold Ranking", Neurocomputing, 312, 239-250, 2018.

[Code][bib]

("*" indicates equal contribution.)


Pichao Wang, Wanqing Li, Zhimin Gao, Chang Tang, Ogunbona Philip, "Depth Pooling Based Large-scale 3D Action Recognition with Convolutional Neural Networks", IEEE Transactions on Multimedia(TMM), 20(5), 1051-1061, 2018.

[Codes:BaiduYun]

[Link][bib]



Chang Tang, Xinwang Liu, Miaomiao Li, Pichao Wang, Jiajia Chen, Lizhe Wang, Wanqing Li, "Robust Unsupervised Feature Selection via Dual Self-representation and Manifold Regularization", Knowledge-Based Systems(KBS), 145, 109-120, 2018.

[Codes:BaiduYun]

[Link][bib]



Chang Tang, Xinzhong Zhu, Jiajia Chen, Pichao Wang, Xinwang Liu, Jie Tian, "Robust Graph Regularized Unsupervised Feature Selection", Expert Systems With Applications(ESWA), 96(C), 64-76, 2018.

[Code]

[Link][bib]

Chang Tang, Lijuan Cao, Xiao Zheng, Minhui Wang, "Gene selection for microarray data classification via subspace learning and manifold regularization", Medical & Biological Engineering & Computing(MBEC), 56(7), 1271–1284, 2018.

[Code][bib]

审稿期刊和目录:

期刊:

IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI)

IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS)

IEEE Transactions on Image Processing (IEEE TIP)

IEEE Transactions on Multimedia (IEEE TMM)

IEEE Transactions on Cybernetics (IEEE TCyB)

IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT)

IEEE Transactions on Cognitive and Developmental Systems (IEEE TCDS)

IEEE Transactions on Signal and Information Processing over Networks

IEEE Transactions on Biomedical Engineering

ACM Transactions on Knowledge Discovery from Data

IEEE Signal Processing Letters(SPL)

Pattern Recognition (PR)

Knowledge-based System (KBS)

Multimedia Tools and Applications(MTAP)

Optics Letters (OL)

Biomedical Optics Express(BOE)


会议:

CVPR

ICCV

AAAI

ICME

IJCAI

NIPS

ICML









  • 教育经历Education Background
  • 工作经历Work Experience
  • 研究方向Research Focus
  • 社会兼职Social Affiliations