Focal Attention Networks: Optimising Attention for Biomedical Image Segmentation

@article{Yeung2022FocalAN,
  title={Focal Attention Networks: Optimising Attention for Biomedical Image Segmentation},
  author={Michael Yeung and Leonardo Rundo and Evis Sala and Carola-Bibiane Sch{\"o}nlieb and Guang Yang},
  journal={2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)},
  year={2022},
  pages={1-5}
}
In recent years, there has been a rising interest to incorporate attention into deep learning architectures for biomedical image segmentation. The modular design of attention mechanisms enable flexible integration into convolutional neural network architectures such as the U-Net. Whether attention is appropriate to use, what type of attention to use, and where in the network to incorporate attention modules, are all important considerations that are currently overlooked. In this paper, we… 

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