Web: http://arxiv.org/abs/2209.10218

Sept. 22, 2022, 1:14 a.m. | Xiangzuo Huo, Gang Sun, Shengwei Tian, Yan Wang, Long Yu, Jun Long, Wendong Zhang, Aolun Li

cs.CV updates on arXiv.org arxiv.org

Medical image classification has developed rapidly under the impetus of the
convolutional neural network (CNN). Due to the fixed size of the receptive
field of the convolution kernel, it is difficult to capture the global features
of medical images. Although the self-attention-based Transformer can model
long-range dependencies, it has high computational complexity and lacks local
inductive bias. Much research has demonstrated that global and local features
are crucial for image classification. However, medical images have a lot of
noisy, scattered …

arxiv classification feature fusion hierarchical image medical network scale

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