Fenglei Xu#, Haokai Zhao#, Fuyuan Hu*, Mingfei Shen, Yifei Wu
CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1559-1570, 2023, DOI:10.32604/cmes.2022.023217
- 27 October 2022
Abstract Convolutional neural networks (CNN) based on U-shaped structures and skip connections play a pivotal role in various image segmentation tasks. Recently, Transformer starts to lead new trends in the image segmentation task. Transformer layer can construct the relationship between all pixels, and the two parties can complement each other well. On the basis of these characteristics, we try to combine Transformer pipeline and convolutional neural network pipeline to gain the advantages of both. The image is put into the U-shaped encoder-decoder architecture based on empirical combination of self-attention and convolution, in which skip connections are More >
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