信 息 科 学 与 工 程 学 院

College of Information Science and Engineering

厚德笃志,勤思敏行

基本信息

basic information

  • 所在院系(中心): 计算机科学与技术系
  • 学历: 博士
  • 政治面貌: 中共党员
  • 邮件地址: gqzhong@ouc.edu.cn
  • 办公电话: 0532-66781719
  • 办公室: 山东省青岛市崂山区松岭路238号中国海洋大学信息科学与工程学院

仲国强

Zhong GuoQiang

课程介绍

course introduction

离散数学 (本科), 机器学习 (本科), 深度学习基础(硕士), 机器学习(博士)

教育及工作经历

education and work experience

2014年3月至今: 由中国海洋大学 "青年英才工程" (第三层次) 项目引进, 副教授, 硕士生导师
2011.10-2013.7: 博士后, 合作导师: Mohamed Cheriet教授, 魁北克大学高等技术学院, 蒙特利尔, 加拿大
2009.9-2010.1: 访问学生, 导师: Dit-Yan Yeung教授, 香港科技大学, 香港, 中国
2007.9-2011.7: 工学博士, 导师: 刘成林研究员, 中国科学院自动化研究所, 北京, 中国
2004.9-2007.7: 理学硕士, 导师: 孟大志教授, 北京工业大学, 北京, 中国
2000.9-2004.7: 理学学士, 河北师范大学, 石家庄, 中国

2015.1至今: ACM会员, IEEE会员, IAPR会员, 中国计算机学会会员, 中国人工智能学会会员, 中国自动化学会会员, 中国图象图形学学会会员
2014.11至今: 中国人工智能学会模式识别专业委员会委员, 中国自动化学会模式识别与机器智能专委会委员, 中国图象图形学学会会员文档图像分析与识别专业委员会委员

研究方向

research direction

人工智能, 机器学习, 模式识别, 计算机视觉, 大数据挖掘, 机器人, 及相关技术的应用.

研究项目

research project

PI6. 基于IPv6和深度学习的网络异常流量监测, 赛尔网络下一代互联网技术创新项目, 项目共同主持人, 2018.1-2018.12.
PI5. 面向自然环境中文字检测与识别的深度网络精简技术研究, CCF-腾讯犀牛鸟创意基金, 项目主持人, 2018.1-2018.12.
PI4. 服务于视障人群的智能穿戴设备研发, 青岛市产业培育计划科技惠民专项, 项目主持人, 2018.1-2019.12.
PI3. 监督的深度学习算法及其在海洋环境数据分析中的应用, 国家自然科学基金青年基金项目(NSFC), 项目主持人, 2015.1 -- 2017.12.
PI2. 深度学习和大规模数据挖掘算法及其应用研究, 中央高校基本科研业务费专项项目("青年英才工程"启动经费), 项目主持人, 2014.3 -- 2019.2.
PI1. 深度小波网络模型及其应用研究, 模式识别国家重点实验室开放课题基金项目, 项目主持人, 2015.1 -- 2016.12. (已结题)
M4. 海洋大数据分析预报技术研发, 国家重点研发计划项目, 参与.
M3. 海洋科学研究中的范式转型与对策研究, 中国海洋发展研究会项目, 参与.
M2. 科技期刊微信平台消息推送的分析与策略, 中国科学技术期刊编辑学会基金项目, 参与.
M1. 海洋锋精细化识别与时空演化的多角度可视化探索, 国家自然科学基金青年基金项目(NSFC), 参与.

PIx: 项目 x 主持人; Mx: 项目 x 参与人.

学术成果

academic achievements

7. 2017, 中国海洋大学本科生毕业论文(设计)优秀指导教师.
6. 2017, 中国大学生“华为杯”智能设计竞赛二等奖, 两项.
5. 2017, 中国大学生“华为杯”智能设计竞赛华为专项奖, 两项.
4. 2015, 中国大学生“华为杯”智能设计竞赛三等奖, 两项.
3. 2014-2015, Outstanding Reviewer Award for the Pattern Recognition journal, Elsevier.
2. 会议(协同)主席: ISSPA2012 poster session chair; IDAS2014 chair; IDAS2015 chair; IJCNN2016 special session chair on Deep Learning for Brain-Like Computing and Pattern Recognition; CAAI-PR Expert Forum program chair (2016); CCF-CV Series Lectures program chair (2016); SFWICT2017 publication chair; ICGIP2017 publication chair等.
1. 期刊会议审稿人: ACM TKDD; IEEE TNNLS; IEEE TCSVT; IEEE Access; PR; Neurocomputing; Cognitive Computation; Neural Computing and applications; 计算机学报; 自动化学报; ICRA2016; ICPR2016等.

论文专利

patent of the paper

部分代表性专著、学术论文和专利如下:

[B2] Guoqiang Zhong and Kaizhu Huang: Semi-Supervised Learning: Background, Applications and Future Directions. Nova Science Publishers, Inc., NY USA. 2018.
[B1] 王勇, 仲国强, 孙鑫: 机器学习导论 (译著). 机械工业出版社. 2016.

[J21] Hongli Miao, Yingting Guo, Guoqiang Zhong, Benxiu Liu, Guizhong Wang: A Novel model of Estimating Sea State Bias Based on Multi-layer Neural Network and Multi-source Altimeter Data. European Journal of Remote Sensing (in press).
[J20] Kaiquan Chen, Yao He, Guoqiang Zhong: The Transformation of Information Literacy Connotation in Artificial Intelligence Perspective and Target Positioning of Artificial Intelligence Education:Also on the Implementation Path of Artificial Intelligence Teaching in Basic Education.Distance Education Journal, 1: 61-71 (2018).
[J19] Guoqiang Zhong, Benxiu Liu, Yingting Guo, Hongli Miao: Sea State Bias Estimation with Least Absolute Shrinkage and Selection Operator (LASSO). Journal of Ocean University of China (in press).
[J18] Guoqiang Zhong, Xiao Ling, Li-Na Wang: From Shallow Feature Learning to Deep Learning: Benefits from the Width and Depth of Deep Architectures. WIREs Data Mining and Knowledge Discovery (in press).
[J17] Qin Zhang, Guoqiang Zhong, Junyu Dong: An Anchor-based Spectral Clustering Method. Frontiers of Information Technology & Electronic Engineering (in press).
[J16] Guoqiang Zhong, Shoujun Yan, Kaizhu Huang, Yajuan Cai, Junyu Dong: Reducing and Stretching Deep Convolutional Activation Features for Accurate Image Classification. Cognitive Computation 10(1): 179-186 (2018).
[J15] Xiaoyi Pan, Jing Wang, Xudong Zhang, Yuan Mei, Lu Shi, Guoqiang Zhong: A Deep Learning Model for the Amplitude Inversion of Internal Waves Based on Optical Remote Sensing Images. International Journal of Remote Sensing (in press).
[J14] Xiaopeng Liu, Guoqiang Zhong, Junyu Dong: Natural Image Illuminant Estimation via Deep Non-negative Matrix Factorisation. IET Image Processing 12(1): 121-125 (2018).
[J13] Qin Zhang, Hui Wang, Junyu Dong, Guoqiang Zhong, Xin Sun: Prediction of Sea Surface Temperature using Long ShortTerm Memory. IEEE Geoscience and Remote Sensing Letters (in press).
[J12] Guoqiang Zhong, Yan Zheng, Sheng Li, Yun Fu: SLMOML: Online Metric Learning with Global Convergence. IEEE Transactions on Circuits and Systems for Video Technology (in press).
[J11] Feng Gao, Xiaopeng Liu, Junyu Dong, Guoqiang Zhong, Muwei Jian: Change Detection in SAR Images Based on Deep Semi-NMF and SVD Networks. Remote Sensing 9 (5): 435 (2017).
[J10] Partha Pratim Roy, Guoqiang Zhong, Mohamed Cheriet: Tandem HMMs Using Deep Belief Networks for Offline Handwriting Recognition. Frontiers of Information Technology and Electronic Engineering 18(7): 978-988 (2017).
[J9] Jianyuan Sun, Guoqiang Zhong, Junyu Dong, Hina Saeeda, Qin Zhang: Cooperative Profit Random Forests With Application in Ocean Front Recognition. IEEE Access 5: 1398-1408 (2017).
[J8] Qin Zhang, Jianyuan Sun, Guoqiang Zhong, Junyu Dong: Random Multi-Graphs: A Semi-Supervised Learning Framework for Classification of High Dimensional Data. Image and Vision Computing 60: 30-37 (2017).
[J7] Xiaopeng Liu, Guoqiang Zhong, Cong Liu, Junyu Dong: Underwater Image Colour Constancy Based on Deep Sparse Nonnegative Matrix Factorization. IET Image Processing 11(1): 38-43 (2017).
[J6] Guoqiang Zhong, Li-Na Wang, Xiao Ling, Junyu Dong: An Overview on Data Representation Learning: From Traditional Feature Learning to Recent Deep Learning. The Journal of Finance and Data Science, 2(4): 265-278 (2016).
[J5] Heng Zhang, Guoqiang Zhong: Improving Short Text Classification by Learning Vector Representations of both Words and Hidden Topics. Knowl.-Based Syst. 102: 76-86 (2016).
[J4] Guoqiang Zhong, Mohamed Cheriet: Tensor representation learning based image patch analysis for text identification and recognition. Pattern Recognition 48(4) : 1207-1220 (2015).
[J3] Guoqiang Zhong, Mohamed Cheriet: Large margin low rank tensor analysis. Neural Computation 26(4) : 761-780 (2014).
[J2] Guoqiang Zhong, Cheng-Lin Liu: Error-correcting output codes based ensemble feature extraction. Pattern Recognition 46(4): 1091-1100 (2013).
[J1] Guoqiang Zhong, Kaizhu Huang, Cheng-Lin Liu: Joint learning of error-correcting output codes and dichotomizers from data. Neural Computing and Applications 21(4): 715-724 (2012).

[C28] Guoqiang Zhong, Hui Yao, Huiyu Zhou: Merging Neurons for Structure Compression of Deep Networks. ICPR, 2018.
[C27] Guoqiang Zhong, Yan Zheng, Xu-Yao Zhang, Hongxu Wei, Xiao Ling: Convolutional Discriminant Analysis. ICPR, 2018.
[C26] Guoqiang Zhong, Hongxu Wei, Yuchen Zheng, Junyu Dong, Mohamed Cheriet: Deep Error Correcting Output Codes. ICPRAI, 2018.
[C25] Qin Zhang, Junyu Dong, Guoqiang Zhong: Visual Texture Perception via Graph-based Semi-supervised Learning. ICGIP, 2017.
[C24] Guoqiang Zhong, Hongxu Wei, Yuchen Zheng, Junyu Dong: Marginal Deep Architectures. ACPR, 2017.
[C23] Yanhai Gan, Huifang Chi, Ying Gao, Jun Liu, Guoqiang Zhong, Junyu Dong: Perception Driven Texture Generation. ICME, 2017.
[C22] Xiaowei Zhou, Guoqiang Zhong, Lin Qi, Junyu Dong,Tuan D. Pham, Jianzhou Mao: Surface Height Map Estimation from a Single Image Using Convolutional Neural Networks. ICGIP, 2016.
[C21] Xuecheng Han, Hui Yao, Guoqiang Zhong: Handwritten Text Line Segmentation by Spectral Clustering. ICGIP, 2016.
[C20] Guoqiang Zhong, Hui Yao, Yutong Liu, Chen Hong, Tuan Pham: Classification of Photographed Document Images Based on Deep-Learning Features. ICGIP, 2016.
[C19] Guoqiang Zhong, Xiao Ling: The necessary and sufficient conditions for the existence of the optimal solution of trace ratio problems. CCPR, 2016.
[C18] Guoqiang Zhong, Yaxin Shi, Mohamed Cheriet: Relational Fisher Analysis: A General Framework for Dimensionality Reduction. IJCNN, 2016
[C17] Guoqiang Zhong, Yan Zheng, Sheng Li, Yun Fu: Scalable Large Margin Online Metric Learning. IJCNN, 2016.
[C16] Guoqiang Zhong, Hui Xu, Pan Yang, Sijiang Wang, Junyu Dong: Deep Hashing Learning Networks. IJCNN, 2016.
[C15] Jianwen Lou, Lin Qi, Junyu Dong, Hui Yu, Guoqiang Zhong: Learning Perceptual Texture Similarity and Relative Attributes from Computational Features. IJCNN, 2016.
[C14] Pan Yang, Haoran Zhao, Lin Qi, Guoqiang Zhong: Self-taught recovery of depth data. APSIPA 2015: 1270-1275.
[C13] Yajuan Cai, Guoqiang Zhong, Yuchen Zheng, Kaizhu Huang, Junyu Dong: Is DeCAF Good Enough for Accurate Image Classification? ICONIP (2) 2015: 354-363.
[C12] Yuchen Zheng, Yajuan Cai, Guoqiang Zhong, Youssouf Chherawala, Yaxin Shi, Junyu Dong: Stretching deep architectures for text recognition. ICDAR 2015: 236-240.
[C11] Guoqiang Zhong, Xin Mao, Yaxin Shi, Junyu Dong: 3D Texture Recognition for RGB-D Images. CAIP (2) 2015: 518-528.
[C10] Chengcheng Jia, Guoqiang Zhong, Yun Raymond Fu: Low-Rank Tensor Learning with Discriminant Analysis for Action Classification and Image Recovery. AAAI 2014: 1228-1234.
[C9] Yuchen Zheng, Guoqiang Zhong, Jun Liu, Xiaoxu Cai, Junyu Dong: Visual Texture Perception with Feature Learning Models and Deep Architectures. CCPR 2014.
[C8] Guoqiang Zhong, Mohamed Cheriet: An empirical evaluation of supervised dimensionality reduction for recognition. ICDAR 2013.
[C7] Guoqiang Zhong, Mohamed Cheriet: Adaptive error-correcting output codes. IJCAI 2013.
[C6] Guoqiang Zhong, Mohamed Cheriet: Image patches analysis for text block identification. ISSPA 2012: 1241-1246.
[C5] Guoqiang Zhong, Kaizhu Huang, Cheng-Lin Liu: Low rank metric learning with manifold regularization. ICDM 2011: 1266-1271.
[C4] Guoqiang Zhong, Wu-Jun Li, Dit-Yan Yeung, Xinwen Hou, Cheng-Lin Liu: Gaussian process latent random field. AAAI 2010.
[C3] Guoqiang Zhong, Kaizhu Huang, Cheng-Lin Liu: Learning ECOC and dichotomizers jointly from data. ICONIP (1) 2010: 494-502.
[C2] Guoqiang Zhong, Xinwen Hou, Cheng-Lin Liu: Relative distance-based Laplacian eigenmaps. CJKPR, 2009.
[C1] Guoqiang Zhong, Lina Wang, Dazhi Meng: The differential geometrical method of modifying SVM and its application in Intron-Extron classification. CCPR, 2007.

[BC4] Guoqiang Zhong, Li-Na Wang, Qin Zhang, Estanislau Lima, Xin Sun, Junyu Dong, Hui Wang, Biao Shen: Oceanic Data Analysis with Deep Learning Models. Deep Learning: Fundamentals, Theory and Applications. 2018.
[BC3] Guoqiang Zhong, Mohamed Cheriet: Low Rank Tensor Manifold Learning. Low-Rank and Sparse Modeling for Visual Analysis, 2014.
[BC2] Mohamed Cheriet, Reza Farrahi Moghaddam, Ehsan Arabnejad Guoqiang Zhong: Manifold learning for the shape-based recognition of historical Arabic documents. Handbook of Statistics: Applications of Machine Learning, 2012.
[BC1] Guoqiang Zhong, Kaizhu Huang, Xinwen Hou, Shiming Xiang: Local tangent space Laplacian eigenmaps. Computational Intelligence, 2012.

[P3] 仲国强, 张康, 凌霄, 洪辰: 基于深度残差网络和支持向量机的物体自动识别系统. 国家发明专利, 申请号:2017108868209.
[P2] 仲国强, 魏洪旭, 王海珍, 孔浩: 基于长短时记忆网络的英文电子邮件写作助手. 国家发明专利, 申请号: 2017107051934.
[P1] 仲国强, 刘汉卿, 庄园, 刘雨桐: 基于规则库的个性化日常陪护机器人自动问答系统. 国家发明专利, 申请号: 2017104973757.

Bx: 专著; Jx: 期刊 x; Cx: 会议 x; BCx: 书的章节 x; Px: 专利 x.

研究生招生条件

postgraduate admissions conditions

已开始接收2019级推免研究生, 欢迎有志于从事人工智能、机器学习、模式识别、计算机视觉、大数据挖掘、机器人等相关方向研究的同学加入我的团队, 要求勤奋、踏实并具有良好的数学、英语运用能力和计算机编程能力, 联系邮箱: gqzhong@ouc.edu.cn.
欢迎中国海洋大学信息科学专业相关的大二、大三年级本科生加入我的研究团队,申请加入团队请先获得两位海大教师的推荐信或三位我的研究团队成员的推荐信,并随自荐信一起发到我的邮箱gqzhong@ouc.edu.cn. 要求:有明确的出国、读博或读研计划,大学期间没有挂科,可以保证平均每周10小时以上的科研时间。

备注

remarks

实验室个人主页: http://cvpr.ouc.edu.cn/people/zhonggq.html.

研究团队毕业生:
序号 姓名 性别 籍贯 在校时间(学位) 现工作单位(现就读学校) 职务 研究方向
1 王私江 男 四川 2011-2015(本科) 百度 高级研发工程师 深度学习、计算广告
2 李东方 男 山东 2012-2016(本科) 哈尔滨工业大学 硕士 NLP & ML
3 范煜璇 女 山东 2012-2016(本科) 渥太华大学 硕士
4 王梦针 女 山东 2012-2016(本科) 南京烽火星空通信发展有限公司 软件工程师
5 赵哲 男 山东 2012-2016(本科) HP Enterprise
6 刘雨桐 女 山东 2013-2017(本科) 上海交通大学 博士 物联网通信
7 韩学成 男 河北 2013-2017(本科) 上海汉得信息技术有限公司 业务咨询顾问
8 庄园 男 广西 2013-2017(本科) 中国科学技术大学 硕士研究生 软件工程
9 刘汉卿 男 山东 2013-2017(本科) 中国科学技术大学 硕士研究生 软件工程
10 杨友钊 男 福建 2013-2017(本科) 复旦大学 硕士研究生 机器学习与计算机视觉
11 石雅欣 女 河北 2014-2017(硕士) 悉尼科技大学 博士 机器学习与数据挖掘
12 张鹏 男 山东 2014-2017(硕士) 青岛港 研发人员 机器学习
13 楚希鹏 男 山东 2014-2017(硕士) 创业 CEO 数据挖掘与机器学习
14 许晖 男 山东 2014-2017(硕士) 中国人民银行济南分行 职员 深度学习、人脸识别
15 郑煜辰 男 湖北 2014-2017(硕士) 日本九州大学 博士 深度学习、文档分析
16 周小伟 男 山东 2014-2017(硕士) 悉尼科技大学 博士 深度学习