[姓名]
魏艳涛

[性别]
男
[教师类型]
湖北省教育信息化研究中心

[是否硕导]
是
[是否博导]
否

[职称]
副教授
[职务]
湖北省教育信息化研究中心副主任

[政治面貌]
中共党员
[电子邮件]
yantaowei@mail.ccnu.edu.cn

[办公电话]

[办公地址]
九号楼730室


[个人简介]
魏艳涛，2012年毕业于华中科技大学图像识别与人工智能研究所（人工智能与自动化学院），副教授，桂子青年****。现主要从事学习分析、人工智能、计算机视觉等方面的研究，主持国家自然科学基金青年基金项目1项，教育部人文社科项目1项，湖北省自然科学基金项目1项，中国博士后科学基金项目1项，中央高校自主科研项目5项。作为主要成员参与国家自然科学基金项目3项、航天“十二五”支撑专题1项，国防预研基金项目1项、航天支撑技术基金项目2项、湖北省自然科学基金项目1项。已在Pattern Recognition、IEEE Transactions on Cybernetics、IEEE Transactions on Geoscience and Remote Sensing、Neurocomputing、Infrared Physics & Technology等国际重要期刊和会议上发表学术论文30余篇，两篇入选ESI高被引论文。被邀请担任IEEE Transactions on Cybernetics、IEEE Transactions on Geoscience and Remote Sensing、IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing、Neurocomputing以及Infrared Physics & Technology等多个国际学术刊物审稿人。


[工作经历]
1、2015.7至今 华中师范大学教育信息技术学院 副教授
2、2017.12-2018.12 美国佛罗里达大学 访问****
3、2015.3-2018.1 华中科技大学 博士后
4、2012.07-2015.06 华中师范大学教育信息技术学院 讲师

[研究方向]
学习分析，人工智能，计算机视觉与机器学习


[近年主持或参与的主要科研项目]
1、基于记忆的不变图像特征学习方法研究，国家自然科学基金青年项目，2016.1-2018.12，主持
2、基于人工智能的在线学习参与度识别研究，教育部人文社科项目，2020.1-2022.12，主持
3、多模态在线学习情感识别与分析，中央高校基本科研业务费青年团队项目，2020.1-2022.12，主持
4、基于I理论的深度学习方法研究，湖北省自然科学基金项目，2018.1-2019.12，主持
5、面向空谱特征学习的深度极限学习方法研究，中央高校基本科研业务费项目，2016.1-2017.12，主持
6、面向图像分类的深度学习方法研究，中央高校基本科研业务费项目，2014.1-2015.12，主持
7、超分辨率中的矩阵值算子学习问题，国家自然科学基金委，2015.1-2018.12，主要成员
8、初等数学问题求解关键技术及系统，863计划子课题，2015.1-2017.12，主要成员

[学术兼职]
1、第23届全球华人计算机教育应用大会子会议主席（学习分析、评估、人工智能教育应用）
2、第22届全球华人计算机教育应用大会子会议副主席（学习分析、评估、人工智能教育应用）
3、中国电子学会现代教育技术分会会员

4、中国自动化学会会员

5、中国计算机学会会员
6、International Journal of Image, Graphics and Signal Processing 杂志编委


[主要论文或专著]
完整文章列表
lZhijing Ye, Jiaqing Chen, Hong Li,Yantao Wei*, Guangrun Xiao, Jón Atli Benediktsson, Supervised functional data discriminant analysis for hyperspectral image classification, IEEE Transactions on Geoscience and Remote Sensing, Vol.58, No.2, pp. 841-851, 2020. (通讯作者，SCI)
l徐家臻，邓伟，魏艳涛.基于人体骨架信息提取的学生课堂行为自动识别,现代教育技术，Vol.30，No.5，pp.108-113, 2020. (CSSCI)
lHuang Yao, Mengting Yang, Tiantian Chen,Yantao Wei*, Yu Zhang, Depth-based human activity recognition via multi-level fused features and fast broad learning system,International Journal of Distributed Sensor Networks, Vol.16, No.2, 2020. (通讯作者，SCI)
lLing Zhong,Yantao Wei*, Huang Yao, Wei Deng, Zhifeng Wang, Mingwen Tong，Review of Deep Learning-Based Personalized Learning Recommendation，Proceedings of the 2020 11th International Conference on E-Education, E-Business, E-Management, and E-Learning，pp. 145-149, 2020.
lYantao Wei, Shujian Yu, Jose C Principe, Multiscale Principle of Relevant Information for Hyperspectral Image Classification, arXiv preprint arXiv:1907.06022, 2019.
l魏艳涛，秦道影，胡佳敏，姚璜*，师亚飞，基于深度学习的学生课堂行为识别，现代教育技术，Vol.29，No.7，pp.87-91, 2019. (CSSCI)
l陈加，张玉麒，宋鹏，魏艳涛*，王煜.深度学习在基于单幅图像的物体三维重建中的应用，自动化学报，Vol.45, No.4, pp.657-668, 2019.
lFen Lei,Yantao Wei*, Jiamin Hu, Huang Yao, Wei Deng, Ying Lu, Student Action Recognition Based on Multiple Features, 2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), pp.428-432, 2019.
lYafei Shi,Yantao Wei*, Donghui Pan, Wei Deng, Huang Yao, Tiantian Chen, Gang Zhao, Mingwen Tong and Qingtang Liu，Student body gesture recognition based on Fisher broad learning system, International Journal of Wavelets, Multiresolution and Information Processing，Vol. 17, No. 1, **,2019.
lShujian Yu, Zubin Abraham, Heng Wang, Mohak Shah,Yantao Wei, José C.Príncipe. Concept drift detection and adaptation with hierarchical hypothesis testing, Journal of the Franklin Institute, Vol. 356, No. 5, pp. 3187-3215, 2019.
l陈甜甜，姚璜，魏艳涛，左明章，杨梦婷，基于融合特征的人体动作识别，计算机工程与设计，pp. 1394-1400，2019.
lYafei Shi,Yantao Wei*, Huang Yao, Donghui Pan, Guangrun Xiao, High-Boost-Based Multiscale Local Contrast Measure for Infrared Small Target Detection, IEEE Geoscience and Remote Sensing Letters 15 (1), 33-37, 2018 (通讯作者，SCI)
lDonghui Pan,Yantao Wei, Houzhang Fang, Wenzhi Yang, A reliability estimation approach via Wiener degradation model with measurement errors, Applied Mathematics and Computation, Vol.320, pp. 131–141, 2018. (SCI)
lJinyan Nie, Shaocheng Qu,Yantao Wei,Liming Zhang, Lizhen Deng, An infrared small target detection method based on multiscale local homogeneity measure, Infrared Physics & Technology 90, 186-194, 2018. (SCI)
lYantao Wei, Peng Zhang, Huang Yao, Jiazhen Xu and Xinge You, Stacked Kernel Extreme Learning Machine for Hyperspectral Image Classification, International Conference on Pattern Recognition and Artificial Intelligence, 2018.
lYantao Wei,Yicong Zhou, Hong Li, Spectral-spatial response for hyperspectral image classification, Remote Sensing, Vol. 9, no. 3, pp.203:1-31, 2017. (SCI)
lYafei Shi，Yantao Wei，Ting Wu，Qingtang Liu，Statistical graph classification in intelligent mathematics problem solving system for high school student，2017 12th International Conference on Computer Science and Education (ICCSE), pp.645-650, 2017.（通讯作者，EI）
lYantao Wei,Yafei Shi, Huang Yao, Gang Zhao and Qingtang Liu, High School Statistical Graph Classification Using Hierarchical Model for Intelligent Mathematics Problem Solving, The Pacific-Rim Symposium on Image and Video Technology (PSIVT), 2017.（EI）
l聂进焱，魏艳涛，瞿少成.一种面向局部神经反应的模板选取算法，计算机工程，Vol.43，No.3, pp. 277-281, 2017.
lYantao Wei, Xinge You, Hong Li, Multiscale Patch-based Contrast Measure for Small Infrared Target Detection, Pattern Recognition, Vol. 58, pp. 216–226, 2016.(SCI, ESI高被引)
lYicong Zhou,Yantao Wei*, Learning Hierarchical Spectral-Spatial Features for Hyperspectral Image Classification, IEEE Transactions on Cybernetics, Vol. 46, pp. 1667-1678, 2016. (通讯作者，SCI,中科院1区，TOP期刊)
lYantao Wei, Xinge You, He Deng, Small Infrared Target Detection Based on Image Patch Ordering, International Journal of Wavelets, Multiresolution and Information Processing, vol. 14, no. 2, pp. 1-14, 2016. (SCI)
lLizhen Deng, Hu Zhu, Chao Tao, andYantao Wei, Infrared Moving Point Target Detection Based on Spatial-temporal Local Contrast Filter, Infrared Physics & Technology vol. 76, pp. 168-173, 2016. (SCI)
lYantao Wei*,Yicong Zhou，Stacked Tensor Subspace Learning for hyperspectral image classification. The 2016 International Joint Conference on Neural Networks, pp. 1985-1992, 2016
lYantao Wei，Guangrun Xiao，He Deng，Hong Chen, Mingwen Tong，Gang，Zhao, Qingtang Liu，Hyperspectral Image Classification Using FPCA-based Kernel Extreme Learning Machine，Optik - International Journal for Light and Electron Optics，vol. 126, no. 23, pp. 3942–3948, 2015. (SCI)
lYuan Yan Tang, Tian Xia,Yantao Wei*, Hong Li, and Luoqing Li, Hierarchical kernel-based rotation and scale invariant similarity, Pattern Recognition, 47(4), pp. 1674–1688, 2014. (通讯作者，SCI)
lC. L. Philip Chen，Hong Li，Yantao Wei, Tian Xia, and Yuan Yan Tang, A local contrast method for small infrared target detection, IEEE Transactions on Geoscience and Remote Sensing, 52(1), pp. 574 - 581, 2014. (SCI)
lHe Deng,Yantao Wei*,Gang Zhao, Qingtang Liu, Integration of local information-based transition region extraction and thresholding, Infrared Physics & Technology, 66, pp. 103 - 113, 2014. (通讯作者，SCI）
lHong Li, Hongfeng Li,Yantao Wei, Yuan Yan Tang, Qiong Wang: Sparse-based neural response for image classification. Neurocomputing 144: 198-207 (2014)
lHong Li,Yantao Wei, Luoqing Li, and C. L. Philip Chen, Hierarchical feature extraction with local neural response for image recognition, IEEE Transactions on Cybernetics, 43(2), pp. 412 - 424, 2013.(SCI)
lHe Deng,Yantao Wei, Mingwen Tong, Small Target Detection Based on Weighted Self-information Map, Infrared Physics & Technology, vol.60, pp. 197-206, 2013. (SCI)
lHe Deng,Yantao Wei, and Mingwen Tong. Background suppression of small target image based on fast local reverse entropy operator, IET Computer Vision, Vol. 7, no. 5, pp. 405 - 413, 2013. (SCI)
l邓鹤，魏艳涛，童名文，瞿少成.基于改进的局部反熵算子的小目标检测,通信学报, Vol. 34, pp. 60-69, 2013.
lHong Li,Yantao Wei, Luoqing Li, and Yuan Yuan, Similarity learning for object recognition based on derived kernel, Neurocomputing, 83(15), pp. 110-120, 2012. (SCI)

[教授课程]
本科生课程：
1、数字图像处理原理
2、计算机技术基础
3、计算机网络
4、Web技术及网站设计与开发
5、Web编程
研究生课程:
1、概率论与数理统计
2、矩阵论与数值分析


[招生信息]
欢迎教育技术、计算机科学与技术、控制科学与工程、数学等相关专业，并具有一定数学和编程基础的有志青年报考，有意报考者请通过电子邮件（yantaowei@mail.ccnu.edu.cn）与我联系。课题组将提供参加国内外学术会议、到境内外研究机构交流访问等多种机会。