个人简介
巫义锐，男，工学博士，河海大学计算机与信息学院副教授，我是水利大数据研究所成员，河海大学计算机视觉实验室(HHU-CV)负责人，获河海大学“大禹学者”称号。研究方向为计算机视觉、多媒体计算与智慧水利。 我于2011年在南京大学计算机科学与技术系获得理学学士学位，同年被保送至南大计算机系攻读博士学位，并于2016年获得工学博士学位，我的指导老师是路通教授， 并和Shivakumara Palaiahnakote教授 保持了紧密合作关系。我曾于2012年和2014年两次访问香港科学与技术大学，并接受了戴秋兰教授和 欧建忠博士的指导。主持了国家自然科学基金、江苏省自然科学基金、国家重点研发计划子专题、国家重点实验室开放课题等多个研究项目。我于权威国际刊物《IEEE Transactions on Image Processing》、《IEEE Transactions on Multimedia》、 《IEEE Transactions on Network Science and Engineering》及高水平国际学术会议ACM Multimedia、 ICME、ICPR、BIBM、ICIP等发表学术论文四十余篇。
我现担任《IET Image Processing》(CCF-C, SCI)的副主编， 《Malaysian Journal of Computer Science》(SCI)的首位外籍副主编， 《Artificial Intelligence and Applications》的创刊副主编， CCF-YOCSEF南京副主席，江苏省信息技术应用学会多媒体专委会副秘书长。我担任过 Journal of Sensor and Actuator Network (JCR Q1)和IEEE COMSOC MMTC Communications-Frontiers的客座主编， ICML2022(CCF-A, 人工智能顶会), ACM MM2022/2021(CCF-A, 多媒体顶会), ICPR2022(CCF-C), ICME2022(CCF-B), HPCC2021(CCF-C), CIKM2021(CCF-B), ACPR2021 等会议程序主席。
您可以下载我的 简历，也可以在知乎上关注我的账号 河海大学巫义锐 或者在学者网上关注我的账号 巫义锐. 请通过wuyirui.github.io关注我的最新信息。
个人资料
- 出生年月： 1989-03
- 学历： 博士研究生毕业
- 毕业院校： 南京大学
教育经历
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2007.09-2011.06,南京大学,计算机科学与技术,理学学士学位
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2011.09-2016.06,南京大学,计算机科学与技术,工学博士学位
科研项目
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1、基于卷积神经网络的场景文字检测模型研究,2017.01.01 00:00:00+00-2018.12.31 00:00:00+00,巫义锐,计算机与软件学院党委、计算机与软件学院
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2、基于文字对称性与上下文关系的自然场景文字检测研究,2017.06.30 00:00:00+00-2019.06.30 00:00:00+00,巫义锐,南京大学（计算机软件新技术国家重点实验室）,计算机与软件学院党委、计算机与软件学院
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3、融合文字对称属性与场景上下文信息的自然场景文字检测研究,2017.07.01 00:00:00+00-2020.06.30 00:00:00+00,巫义锐,江苏省科学技术厅,计算机与软件学院党委、计算机与软件学院
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4、基于文字对称性与场景上下文信息的自然场景文字检测研究,2018.01.01 00:00:00+00-2020.12.31 00:00:00+00,巫义锐,国家自然科学基金委员会,计算机与软件学院党委、计算机与软件学院
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5、大数据驱动的流域智能管理与决策关键技术—课题1：流域水资源管理的大数据分析理论与技术,2018.07.01-,科学技术部,计算机与信息学院
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6、智能横幅广告排版技术开发,2018.12.01 00:00:00+00-2019.01.31 00:00:00+00,巫义锐,杭州全速网络技术有限公司,计算机与软件学院党委、计算机与软件学院
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7、智能横幅广告排版技术开发（二期）,2019.04.08 00:00:00+00-2019.07.31 00:00:00+00,巫义锐,杭州全速网络技术有限公司,计算机与软件学院党委、计算机与软件学院
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8、智能横幅广告排版技术开发（二期）,2019.04.08 00:00:00+00-2019.07.31 00:00:00+00,巫义锐,杭州全速网络技术有限公司,计算机与软件学院党委、计算机与软件学院
论文
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1、A Robust Symmetry-Based Method for Scene/Video Text Detection through Neural Network,2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR),12-OCT-17
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2、Deep-dense Conditional Random Fields for Object Co-segmentation,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17),04-MAY-17
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3、Multi-Glimpse LSTM With Color-Depth Feature Fusion For Human Ddetetion,2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings,14-SEP-17
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4、Compressing YOLO Network by Compressive Sensing,The 4th Asian Conference on Pattern Recognition(ACPR'17),18-OCT-17
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5、Cloud of Line Distribution and Random Forest Text Detection from Natural/Video Scene Images,The 24th International Conference on Multimedia Modeling(MMM'18),03-MAR-18
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6、A Novel 3D Human Action Recognition Framework for Video Content Analysis,The 24th International Conference on Multimedia Modeling(MMM'18),03-MAR-18
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7、Local and global Bayesian network based model for flood prediction,The 24th International Conference on Pattern Recognition (ICPR'18),01-SEP-18
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8、Context-aware attention LSTM network for flood prediction,The 24th International Conference on Pattern Recognition,01-SEP-18
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9、Em-SLAM: a fast and robust monocular SLAM method for embedded systems,The 24th International Conference on Pattern Recognition (ICPR'18),01-SEP-18
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10、End-to-end chromosome karyotyping with data augmentation using GAN,The 25th IEEE International Conference on Image Processing (ICIP),06-OCT-18
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11、Hierarchical Bayesian network based incremental model for flood predicition,The 25th International Conference on Multimedia Modeling (MMM'19),02-DEC-18
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12、Context and Temporal Aware Attention Model for Flood Prediction,PCM 2018 - 19th Pacific-Rim Conference on Multimedia,23-SEP-18
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13、A New COLD Feature based Handwriting Analysis for Ethnicity/Nationality Identification,The 16th International Conference on Frontiers in Handwriting Recognition,17-OCT-18
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14、Compressive Sensing Based Convolutional Neural Network for Object Detection,Malaysian Journal of Computer Science,15-MAR-18
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15、基于网络爬虫的水利信息检索系统的设计与实现,水利信息化,09-AUG-17
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16、Hierarchical Bayesian Network Based Incremental Model for Flood Prediction,Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),01-JAN-19
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17、CASR: a context-aware residual network for single-image super-resolution,Neural Computing and Applications,01-JAN-19
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18、Sparse Bayesian flood forecasting model based on smoteboost,Proceedings - 2019 IEEE International Congress on Cybermatics: 12th IEEE International Conference on Internet of Things, 15th IEEE International Conference on Green Computing and Communications, 12th IEEE International Conference on Cyber, Physical and Social Computing and 5th IEEE International Con,01-JAN-19
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19、Deep learning methods in real-time image super-resolution: a survey,Journal of Real-Time Image Processing,01-JAN-19
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20、Em-SLAM: A Fast and Robust Monocular SLAM Method for Embedded Systems,Proceedings - International Conference on Pattern Recognition,01-JAN-18
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21、Compressing YOLO network by compressive sensing,Proceedings - 4th Asian Conference on Pattern Recognition, ACPR 2017,01-JAN-18
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22、Context-Aware Attention LSTM Network for Flood Prediction,Proceedings - International Conference on Pattern Recognition,01-JAN-18
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23、Local and Global Bayesian Network based Model for Flood Prediction,Proceedings - International Conference on Pattern Recognition,01-JAN-18
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24、End-To-End Chromosome Karyotyping with Data Augmentation Using GAN,Proceedings - International Conference on Image Processing, ICIP,01-JAN-18
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25、Spatio-Temporal attention lstm model for flood forecasting,Proceedings - 2019 IEEE International Congress on Cybermatics: 12th IEEE International Conference on Internet of Things, 15th IEEE International Conference on Green Computing and Communications, 12th IEEE International Conference on Cyber, Physical and Social Computing and 5th IEEE International Con,01-JAN-19
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26、Deep spatiotemporal LSTM network with temporal pattern feature for 3D human action recognition,COMPUTATIONAL INTELLIGENCE,01-JAN-19
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27、Network Attacks Detection Methods Based on Deep Learning Techniques: A Survey,SECURITY AND COMMUNICATION NETWORKS,01-JAN-20
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28、A New Multiple-Distribution GAN Model to Solve Complexity in End-to-End Chromosome Karyotyping,COMPLEXITY,01-JAN-20
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29、SMOTE-Boost-based sparse Bayesian model for flood prediction,EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING,01-JAN-20
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30、Complexity to Forecast Flood: Problem Definition and Spatiotemporal Attention LSTM Solution,COMPLEXITY,01-JAN-20
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31、Attention Neural Network for Water Image Classification under IoT Environment,APPLIED SCIENCES-BASEL,01-JAN-20
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32、COMPRESSIVE SENSING BASED CONVOLUTIONAL NEURAL NETWORK FOR OBJECT DETECTION,MALAYSIAN JOURNAL OF COMPUTER SCIENCE,01-JAN-20
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33、CASR: a context-aware residual network for single-image super-resolution,NEURAL COMPUTING & APPLICATIONS,01-JAN-20
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34、Deep learning methods in real-time image super-resolution: a survey,JOURNAL OF REAL-TIME IMAGE PROCESSING,01-JAN-20
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35、A Robust Symmetry-Based Method for Scene/Video Text Detection through Neural Network,2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR),2017-10-12,计算机与软件学院党委、计算机与软件学院
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36、Deep-dense Conditional Random Fields for Object Co-segmentation,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17),2017-05-04,计算机与软件学院党委、计算机与软件学院
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37、Deep-dense Conditional Random Fields for Object Co-segmentation,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17),2017-05-04,计算机与软件学院党委、计算机与软件学院
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38、Multi-Glimpse LSTM With Color-Depth Feature Fusion For Human Ddetetion,2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings,2017-09-14,计算机与软件学院党委、计算机与软件学院
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39、Compressing YOLO Network by Compressive Sensing,The 4th Asian Conference on Pattern Recognition(ACPR'17),2017-10-18,计算机与软件学院党委、计算机与软件学院
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40、Cloud of Line Distribution and Random Forest Text Detection from Natural/Video Scene Images,The 24th International Conference on Multimedia Modeling(MMM'18),2018-03-03,计算机与软件学院党委、计算机与软件学院
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开授课程
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1、数字图像处理,本科生,101,32
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2、数字图像处理,研究生,11,32
招生信息
课题组正招收，有兴趣从事计算机视觉、人工智能、视频与图像数据处理、模式识别与计算机图形学研究及技术开发的学生。请通过邮箱 wuyirui@hhu.edu.cn联系我。
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