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This work was supported by the National Natural Science Foundation of China (Grant No. 62076124).
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Songcan Chen received his BS degree in mathematics from Hangzhou University (now merged into Zhejiang University), China in 1983. In 1985, he completed his MS degree in computer applications at Shanghai Jiaotong University and then worked at NUAA in January 1986. There he received a PhD degree in communication and information systems in 1997. Since 1998, as a full-time professor, he has been with the College of Computer Science & Technology at NUAA, China. His research interests include pattern recognition, machine learning and neural computing. He is also an IAPR Fellow.
Chuanxing Geng respectively received the BS degree in mathematics from Liaocheng University, China in 2013 and the MS degree in applied mathematics from Ningbo University, China in 2016. In 2020, he received the PhD degree with the College of Computer Science & Technology from Nanjing University of Aeronautics and Astronautics, China. His research interests include pattern recognition and machine learning.
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Chen, S., Geng, C. A comprehensive perspective of contrastive self-supervised learning. Front. Comput. Sci. 15, 154332 (2021). https://doi.org/10.1007/s11704-021-1900-9
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DOI: https://doi.org/10.1007/s11704-021-1900-9