師資隊伍


教师信息                                                                                                                                                 个人照片      
姓    名趙仲秋性    別 男
出生年月1977年9月最終學位博士                  
畢業學校中國科技大學
從事專業模式识别与智能系统                    職    務博士生導師
所屬院系計算機科學與技術系
所屬科室(研究所)计算机软件与理论研究所                     職     稱 研究員
聯系方式

辦公電話:0551-62902575

E-mail: zhongqiuzhao AT gmail DOT com

通訊地址

郵  編
簡    曆

江苏靖江人;工学博士,研究员,博士生導師;IEEE/ACM会员。

-2007年12月~2008年3月在合肥工業大學計算機與信息學院“圖像信息處理研究室”從事研究工作;
-2008年4月~2009年11月于法国 UNIVERSITE PAUL CEZANNE – AIX-MARSEILLE III 任博士后;
-2009年12月至今,于合肥工業大學計算機與信息學院工作,2011年12月入選合肥工業大學計算機與信息學院人才培育“C計劃”。
-2012年入選“香江學者”計劃,2013年1月~2014年12月于香港浸會大學計算機科學系從事合作研究。

近年來主持國家自然科學基金項目3項,教育部高等學校博士點新教師基金、中國博士後科學基金特別資助等各1項;承擔科技部863項目、973課題、973前期預研專項項目、法國國家科研署(ANR)項目等多個項目的研究。

在相關領域已經發表論文50余篇,包括IEEE TNNLSIEEE TIPIEEE ToCIEEE TKDEPRIEEE MultimediaNeurocomputingPRL 等權威學術期刊,以及IJCAIECCVACM MIRACCVICIP 等權威學術會議。获授权国家发明專利5項。

担任IEEE Trans. Evolutionary Computation, IEEE Trans. Multimedia, IEEE Trans. Image Processing, IEEE TNNLS,Computer Vision and Image Understanding,Pattern Recognition Letters, 《计算机学报》等期刊的论文审稿人。

研究方向

研究方向包括:模式識別、深度學習、圖像視頻分類與理解、數據挖掘等。

歡迎具有良好數學基礎、有志于從事圖像和視頻處理技術應用研究的學生報考研究生!理想和態度決定您的高度!

主持科研項目:

(1)安徽省傑出青年科學基金,圖像分類和標注中的稀疏感知問題No. 170808J082017.1.1-2019.12

(2)國家自然科學基金面上項目,“增長的卷積神經網絡模型中的若幹關鍵問題研究”,

   (No. 61672203,2017.1-2020.12

(3)國家自然科學基金面上項目,“基于耦合判別和協作稀疏表示的圖像表征和標注研究”,

   (No. 61375047,2014.1 - 2017.12)

(4)“香江學者”計劃,“高維數據下的特征選擇及應用”,

   (No. XJ2012012,2013.1 - 2014.12)

(5)國家自然科學基金青年基金,“約束最大差異投影在基于內容的多樣化圖像檢索中的應用研究”

   (No. 61005007, 2011.1 - 2013.12)

(6)教育部高等學校博士點新教師基金,“基于子域模塊分類器的非對稱模式分類研究”

   (No. 200803591024,2009.1 - 2011.12)

教學工作

《人工神經網絡》 
《智能信息處理》 
《程序設計基礎》
獲獎情况

2012年入選“香江學者”計劃;
2014年獲ACM南京分會(江蘇、安徽地區)卓越青年科學家獎提名獎;
2016年獲安徽省傑出青年科學基金資助;
2016年獲教育部自然科學一等獎;

2018年獲吳文俊人工智能科學技術獎科技進步一等獎

主要論著
 

[28] Z.Q. Zhao, P. Zheng,S. Xu, X. Wu, Object Detection with Deep Learning: A Review, DOI: 10.1109/TNNLS.2018.2876865, IEEE Transactions on Neural Networks and Learning Systems, 2019.   

[27] Z.Q. Zhao, J. Hu; W. Tian, N. Ling, Cooperative Adversarial Network for Accurate Super Resolution, Asian Conference on Computer Vision (ACCV), 2018.

[26] P. Zheng, Z.Q. Zhao*, J. Gao, X. Wu, A set-level joint sparse representation for image set classification, Information Sciences, Vol. 448–449,pp.75–90, June 2018. (*corresponding author

[25] P. Zheng, Z.Q. Zhao*, J. Gao, X. Wu, Image set classification based on cooperative sparse representation, Pattern Recognition, Volume 63, Pages 206–217,March 2017. (*corresponding author)

[24] D. Hu, X. Zhang, Y. Fan, Z.Q. Zhao, L. Wang, X. Wu, X. Wu,  On Digital Image Trustworthiness, Applied Soft Computing, Vol. 48, pp.240-253, 2016. 

[23] Z.Q. Zhao, Y. Cheung, H. Hu, X. Wu, Corrupted and Occluded Face Recognition via Cooperative Sparse Representation, Pattern Recognition, Vol. 56, Pages 77–87, August, 2016.

[22] S. Li, Z.H. You, H. Guo, X. Luo, Z.Q. Zhao, Inverse-Free Extreme Learning Machine With Optimal Information Updating, IEEE Transactions on Cybernetics, vol.46,issue 5, pp.1229-1241, 2016.
[21] 
Z.Q. Zhao, Y. Cheung, H. Hu, X. Wu, Expanding dictionary for robust face recognition: pixel is not necessary while sparsity is, IET Computer Vision, Vol. 9(5),pp.648 –654, 2015.

[20] X. Wu, H. Chen, G.Q. Wu, J. Liu, Q. Zheng, X. He, A. Zhou, Z.Q. Zhao, B. Wei, Y. Li, Q. Zhang, S. Zhang: Knowledge Engineering with Big Data.IEEE Intelligent Systems, 30(5): 46-55 (2015)
[19] 
Z.Q. Zhao, Y. Hong, P. Zheng, X. Wu: Plant identification using triangular representation based on salient points and margin points. ICIP 2015: 1145-1149

[18] Z.Q. Zhao, L.H. Ma, Y. Cheung, X. Wu, Y. Tang, C.L.P. Chen, ApLeaf: An efficient android-based plant leaf identification system, Neurocomputing, Volume 151, Part 3, 3 March 2015, Pages 1112-1119.

[17] J. Wang, M. Wang, P.P. Li, L. Liu, Z.Q. Zhao, X. Hu, X. Wu: Online Feature Selection with Group Structure Analysis. IEEE Transactions on Knowledge and Data Engineering, 27(11): 3029-3041 (2015)

[16] Z.Q. Zhao, B.J. Xie, Y. Cheung, X. Wu, Plant Leaf Identification via A Growing Convolution Neural Network with Progressive Sample Learning, ACCV, 2014.

[15] 趙仲秋, 季海峰, 高隽, 胡東輝, 吴信东. 基于稀疏编码多尺度空间潜在语义分析的图像分类,《计算机学报》, 37(6): 1251-1260, 2014.

[14] Z.Q. Zhao, XinDong Wu, CanYi Lu, Herve Glotin, Jun Gao, Optimizing widths with PSO for center selection of Gaussian radial basis function networks,SCIENCE CHINA Information Sciences, Volume 57, Issue 5, pp 1-17, May 2014. DOI: 10.1007/s11432-013-4850-5

[13] Bo Li, Jin Liu, Z.Q. Zhao and Wen-Sheng Zhang, Locally Linear Representation Fisher Criterion, International Joint Conference on Neural Networks (IJCNN), 2013. 

[12] J. Wang, Z.Q. Zhao, X. Hu, Y. Cheung, M. Wang, and X. Wu, Online Group Feature Seclection, 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013. 

[11] Z.Q. Zhao, H. Glotin, Z. Xie, J. Gao, and X. Wu, Cooperative Sparse Representation in Two Opposite Directions for Semi-supervised Image Annotation, IEEE Transactions on Image Processing (TIP), Vol. 21 , Issue 9, pp. 4218 - 4231, 2012 (regular paper).

[10] Can-Yi Lu, Hai Min, Zhong-Qiu Zhao, Lin Zhu, De-Shuang Huang, Shuicheng Yan, Robust and Efficient Subspace Segmentation via Least Squares Regression,European Conference on Computer Vision (ECCV), 2012.(top conference)

[9]  Z.Q. Zhao, J.Z. Li , J. Gao, X.D. Wu, “A Modified Semi-Supervised Learning Algorithm on Laplacian Eigenmaps,” Neural Processing Letters,  vol. 32(1), 76-82, 2010. 

[8]  Z.Q. Zhao, J. Gao, H. Glotin, X.D. Wu, “A matrix modular neural network based on task decomposition with subspace division by adaptive affinity propagation clustering,”Applied Mathematical Modelling, 34, pp. 3884–3895, 2010. 

[7]  H. Glotin, Z.Q. Zhao, J. Gao, X.D. Wu, “A Matrix Modular SVM Robust to Imbalanced Dataset for Efficient Visual Concept Detections,” The 11th ACM SIGMM International Conference on Multimedia Information Retrieval (ACM MIR 2010), March 29-31, 2010, National Constitution Center, Philadelphia, Pennsylvania, USA. 
[6]  
Z.Q. Zhao, H. Glotin, “Diversifying Image Retrieval by Affinity Propagation Clustering on Visual Manifolds,” IEEE Mutimedia, vol. 16, no. 4, pp. 34-43, 2009. 
[5]  
Z.Q. Zhao, “A Novel Modular Neural Network for Imbalanced Classification Problems,” Pattern Recognition Letters, Vol.30, No.9, pp. 783-788, 2009. 
[4]  
Z.Q. Zhao, D.S. Huang, and W. Jia, “Palmprint Recognition with 2DPCA+PCA Based on Modular Neural Networks,” Neurocomputing,Vol. 71(1-3), pp. 448-454, 2007. 
[3]  
Z.Q. Zhao and D.S. Huang, “A mended hybrid learning algorithm for radial basis function neural networks to improve generalization capability,”Applied Mathematics Modelling,Vol. 31(7), pp. 1271-1281, 2007. 
[2]  
Z.Q. Zhao, D.S. Huang, B. Y.  Sun,  “Human face recognition based on multiple features using neural networks committee,”  Pattern Recognition Letters, Vol.25(12), pp.1351-1358, 2004.

[1]  H. Glotin, Z.Q. Zhao, S. Ayache, “Efficient Image Concept Indexing by Harmonic and Arithmetic Profiles Entropy,” Proceedings of 2009 IEEE International Conference on Image Processing (ICIP 2009), IEEE Signal Processing Society, pp.277-280, 2009