Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (1)
  • Open Access


    A Road Segmentation Model Based on Mixture of the Convolutional Neural Network and the Transformer Network

    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

    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 utilized for local-global semantic feature… More >

Displaying 1-10 on page 1 of 1. Per Page  

Share Link