Study

Title
Professor, Doctoral & Graduate Supervisor, School of future technology
auwxkang@scut.edu.cn
Honor
Member of the Pattern Recognition Committee of the Chinese Association for Artificial Intelligence, Member of the Intelligent Interaction Committee of the Chinese Association for Artificial Intelligence, Member of the Pattern Recognition and Machine Intelligence Committee of the Automation Society, Member of the Hybrid Intelligence Committee of the Automation Society, Member of the Visual Big Data Committee of the Chinese Society for Image and Graphics, Member of the Education Working Committee of the Chinese Association for Artificial Intelligence (for the second term), Standing Committee Member of the Seventh Committee of the Science and Technology Association of Tianhe District, Guangzhou City
MEng: 1) Electronic Information
Kang Wenxiong, a professor at South China University of Technology and a doctoral supervisor, is the dean of the School of Automation at Guangdong University of Petrochemical Technology (on secondments) and the deputy director of the Guangdong Provincial Key Laboratory of Intelligent Finance Enterprises. Director of the South China University of Technology - Benliu Electric Power Artificial Intelligence Joint Laboratory, and Head of the Biometric Recognition and Intelligent Perception Laboratory (BIPLAB) of South China University of Technology; Member of IEEE, ACM, CCF, Member of the Pattern Recognition Special Committee of the Chinese Association for Artificial Intelligence, Member of the Intelligent Interaction Special Committee of the Chinese Association for Artificial Intelligence, Member of the Pattern Recognition and Machine Intelligence Special Committee of the Chinese Association for Automation, Member of the Hybrid Intelligence Professional Committee of the Chinese Association for Automation, Member of the Visual Big Data Special Committee of the Chinese Society for Image and Graphics Member of the Second Committee of the Education Work Committee of the Chinese Association for Artificial Intelligence and Standing Committee Member of the Seventh Committee of the Science and Technology Association of Tianhe District, Guangzhou City. From September 2009 to June 2016 and from November 2016 to December 2017, I conducted visiting research at the Swiss Federal University of Technology in Zurich and the University of Sydney in Australia respectively as a researcher and a visiting scholar. Current main research interests: Image processing and pattern recognition, computer vision, natural language processing, biometric recognition, deep learning.
Image processing and pattern recognition, computer vision, natural language processing, biometric recognition, deep learning
Y. Zhang, X. Wang, M. Shakeel, H. Wan, W. Kang*, Learning Upper Patch Attention using Dual-branch training strategy for Masked Face Recognition, Pattern Recognition, Accept (SCI IF=3.965,JCR Q1)
J. Huang, M. Tu, W. Yang and W. Kang*, Joint Attention Network for Finger Vein Authentication. IEEE Transactions on Instrumentation and Measurement, vol. 70, pp. 1-11, 2021, doi: 10.1109/TIM.2021.3109978.
Z. Zhang, F. Zhong and W. Kang*, Study on Reflection-Based Imaging Finger Vein Recognition, IEEE Transactions on Information Forensics and Security, doi: 10.1109/TIFS.2021.3093791.
W. Jia, W. Xia, B. Zhang, Y. Zhao, L. Fei, W. Kang, D. Huang, G. Guo, A survey on dorsal hand vein biometrics,Pattern Recognition 120, 108122 (SCI IF=3.965,JCR Q1)
H. Xu, L. Wang, Q. Wu, W. Kang*. PVLNet: Parameterized-View-Learning neural network for 3D shape recognition. Computers & Graphics. 98: 71-81 (2021)
H. Xu, W. Yang, Q. Wu, W. Kang*,Endowing Rotation Invariance for 3D Finger Shape and Vein Verification,Frontiers of Computer Science, Accept (SCI )
J.Xu, H. Tian , Z. Wang, Y. Wang, W. Kang, F.Chen,Joint Input and Output Space Learning for Multi-Label Image Classification. IEEE Transactions on Multimedia. 23: 1696-1707 (2021) (SCI IF=3.977,JCR Q1)
C. Liu , Y. Yang, X. Liu, L. Fang, and W. Kang*, Dynamic Hand Gesture Authentication Dataset and Benchmark, IEEE Transactions on Information Forensics and Security, 2021(16): 1550-1562. (SCI IF=5.824,JCR Q1)