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UPANets: Learning from the Universal Pixel Attention Networks [article]

Ching-Hsun Tseng, Shin-Jye Lee, Jia-Nan Feng, Shengzhong Mao, Yu-Ping Wu, Jia-Yu Shang, Mou-Chung Tseng, Xiao-Jun Zeng
2021 arXiv   pre-print
Recently, from the successful development of multi-head attention in natural language processing, it is sure that now is a time of either using a Transformer-like model or hybrid CNNs with attention.  ...  Also, the extreme-connection structure makes UPANets robust with a smoother loss landscape.  ...  By integrating proposed methods into a networks, our UPANets can additionally process universal pixels with CNNs and CPA, reuse feature maps by denselyconnection, residual learning with skip-connection  ... 
arXiv:2103.08640v2 fatcat:jlh6oumobzfbfgjzbsgx6gjdte