以第一作者和通讯作者发表论文列表:
[1] Yuanyun Wang, Wenshuang Zhang, Changwang Lai, Jun Wang*, Adaptive temporal feature modeling for visual tracking via cross-channel learning, Knowledge-based Systems, 265 (2023) 110380, http://doi.org/10.1016/j.knosys.2023. 110380. (SCI一区)
[2] Jun Wang, Chenchen Meng, Chengzhi Deng, and Yuanyun Wang, Learning Attention Models for Visual Tracking, Signal, Image and Video Processing, 2022, DOI:10.1007s11760-022-02177-4. (SCI)
[3] Jun Wang, Chenchen Meng, Chengzhi Deng, and Yuanyun Wang, Learning convolutional self-attention module for unmanned aerial vehicle tracking, Signal, Image and Video Processing, 2022, https://doi.org/10.1007/s11760-022-02449-z. (SCI )
[4] Chenchen Meng, Jun Wang*, Chengzhi Deng, Yuanyun Wang, and Shengqian Wang*, Convolutional Neural Networks based Dictionary Pair Learning for Visual Tracking, IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, Vol. E105-A, No.8, pp.1-10, Aug. 2022. (SCI)
[5] Jun Wang, Limin Zhang, Wenshuagn Zhang, Yuanyun Wang, Chengzhi Deng, SGAT: Shuffle and Graph Attention based Siamese Networks for Visual Tracking, PLOS One, 17(11), 2022, 10.1371/journal.pone.0277064. (SCI)
[6] Jun Wang, Limin Zhang, Yuanyun Wang, Changwang Lai, Wenhui Yang, Chengzhi Deng, SiamLST: Learning Spatial and Channel-wise Transform for Visual Tracking, Tehnički vjesnik-Technical Gazette, 29 (4), 2022: pp. 1202-1209. (SCI)
[7] Yuanyun Wang, Wenshuang Zhang, Limin Zhang, Jun Wang*, Siamese Network with a Depthwise Over-parameterized Convolutional Layer for Visual Tracking, PLOS One, 17 (8), 2022: pp. 1-21. (SCI)
[8] Jun Wang,Yuanyun Wang, and Hanzi Wang, Adaptive appearance modeling with point-to-set metric learning for visual tracking, IEEE Transactions on Circuits and Systems for Video Technology, 27(9), 2017, pp. 1987-2000. (SCI.)
[9] Jun Wang, Hanzi Wang, and Yan Yan, Robust visual tracking by metric learning with weighted histogram representations, Neurocomputing, 153 (2015): 77-88. (SCI)
[10] Jun Wang, Hanzi Wang, Wan-Lei Zhao, Affine Hull based Target Representation for Visual Tracking, Journal of Visual Communication and Image Representation, 30(2015) : 266-276. (SCI )
[11] Jun Wang, Yuanyun Wang, Chengzhi Deng*, Shengqian Wang, and Yong Qin, Regularized Kernel Representation for Visual Tracking, IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, Vol. E101-A, No.4, pp.668-677, Apr. 2018. (SCI)
[12] Jun Wang, Yuanyun Wang, Chengzhi Deng*, and Shengqian Wang, Robust visual tracking based on Convex hull with EMD-L1, Pattern Recognition and Image Analysis, 28(1), 2018, pp. 44-52. (EI)
[13] Jun Wang, Yuanyun Wang, Ke Wang, and Chengzhi Deng*, L1 regularized hull representation for visual tracking, Journal of Information Hiding and Multimedia Signal Processing, 9(2),2018, pp. 313-324. (EI)
[14] Jun Wang,Yuanyun Wang, Chengzhi Deng, Huasheng Zhu and Shengqian Wang, Convex hull for visual tracking with EMD, IEEE International Conference on Audio, Language and Image Processing, 2016, pp. 433-437. (EI)
[15] Jun Wang,Yuanyun Wang, Chengzhi Deng, Huasheng Zhu, Shengqian Wang and Li Lv, Sparse affine hull for visual tracking, International Conference on Digital Home, 2016, pp. 85-88. (EI)
[16] Jun Wang, Yuanyun Wang, Chengzhi Deng*, and Shengqian Wang, Kernelized convex hull for visual tracking, International Conference on progress in informatics and computing, 2017, 159-163. (EI)
[17] Jun Wang, Yuanyun Wang, Shaoquan Zhang, Chenguang Xu, Chengzhi Deng, Dictionary Learning for Visual Tracking with Dimensionality Reduction, IEEE International Conference on Image, Vision and Computing, 2020, pp.251-255. (EI)
[18] Jun Wang, Zhanghua Wang, Shuaibin Xi, Yuanyun Wang*, Chenguang Xu, and Jun Zhang, Bayesian Matrix Factorization for Visual tracking, International Conference on progress in informatics and computing, 2020, pp. 89-93. (EI)
[19] Jun Wang, Limin Zhang, Yuanyun Wang, Wenshuang Zhang, Changwang Lai, Chengzhi Deng, Learnable Sparse Transform Siamese Attention Networks for Visual Tracking, International Conference on Computer Engineering and Artificial Intelligence, 2021, pp. 350-354. (EI)
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