中國海洋大學信息科學與工程學院教師，副教授，碩士生導師，主要研究方向為深度學習。
基本介紹
- 中文名：仲國強
- 職業：高校教師
- 學歷：博士
- 性別：男
教育及工作經歷,研究方向,科研項目,論文專利,
教育及工作經歷
2014年3月由中國海洋大學 "青年英才工程" (第三層次) 項目引進
2011.10-2013.7: 博士後, 導師: Mohamed Cheriet教授, 魁北克大學高技術學院, 蒙特婁, 加拿大
2011.2-2011.5: 實習研究員, 中國三星技術院, 北京, 中國
2009.9-2010.1: 訪問學生, 導師: Dit-Yan Yeung教授, 香港科技大學, 香港, 中國
2007.9-2011.7: 工學博士, 導師: 劉成林研究員, 中國科學院自動化研究所, 北京, 中國
2004.9-2007.7: 理學碩士, 導師: 孟大志教授, 北京工業大學, 北京, 中國
2000.9-2004.7: 理學學士, 河北師範大學, 石家莊, 中國
2015.1至今: 中國計算機學會會員, ACM會員, IEEE會員
2014.11至今: 中國人工智慧學會會員, 中國人工智慧學會模式識別專業委員會委員
2011.10-2013.7: 博士後, 導師: Mohamed Cheriet教授, 魁北克大學高技術學院, 蒙特婁, 加拿大
2011.2-2011.5: 實習研究員, 中國三星技術院, 北京, 中國
2009.9-2010.1: 訪問學生, 導師: Dit-Yan Yeung教授, 香港科技大學, 香港, 中國
2007.9-2011.7: 工學博士, 導師: 劉成林研究員, 中國科學院自動化研究所, 北京, 中國
2004.9-2007.7: 理學碩士, 導師: 孟大志教授, 北京工業大學, 北京, 中國
2000.9-2004.7: 理學學士, 河北師範大學, 石家莊, 中國
2015.1至今: 中國計算機學會會員, ACM會員, IEEE會員
2014.11至今: 中國人工智慧學會會員, 中國人工智慧學會模式識別專業委員會委員
研究方向
人工智慧, 模式識別和機器學習, 特別是深度學習, 相關的理論與算法及其在圖像處理, 文檔分析, 數據挖掘中的套用研究.
科研項目
3. 深度小波網路模型及其套用研究, 模式識別國家重點實驗室開放課題基金項目, 項目主持人, 2015.1 -- 2016.12.
2. 監督的深度學習算法及其在海洋環境數據分析中的套用, 國家自然科學基金青年基金項目(NSFC), 項目主持人, 2015.1 -- 2017.12.
1. 深度學習和大規模數據挖掘算法及其套用研究, 中央高校基本科研業務費專項項目, 項目主持人, 2014.3 -- 2019.2.
2. 監督的深度學習算法及其在海洋環境數據分析中的套用, 國家自然科學基金青年基金項目(NSFC), 項目主持人, 2015.1 -- 2017.12.
1. 深度學習和大規模數據挖掘算法及其套用研究, 中央高校基本科研業務費專項項目, 項目主持人, 2014.3 -- 2019.2.
論文專利
[J5] Partha Roy, Guoqiang Zhong, Mohamed Cheriet: Tandem HMMs using Deep Belief Networks for Offline Handwriting Recognition. Pattern Recognition Letter (under review).
[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).
[C10] Guoqiang Zhong, Sheng Li, Yun Fu: Scalable large margin online metric learning. (under review).
[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.
[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.
Jx: 期刊 x; Cx: 會議 x; BCx: 書的章節 x.
[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).
[C10] Guoqiang Zhong, Sheng Li, Yun Fu: Scalable large margin online metric learning. (under review).
[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.
[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.
Jx: 期刊 x; Cx: 會議 x; BCx: 書的章節 x.
