$\uparrow 11.80$ %). By comparing visualization results, our proposed DCA-DAFFNet can pay more attention to the heterogeneous nuclei (polymorphic-nucleus, mega-nucleus, and so on) concerned by pathologists, which shows that our method is more interpretable and human-computer interactive.">

DCA-DAFFNet: An End-to-End Network With Deformable Fusion Attention and Deep Adaptive Feature Fusion for Laryngeal Tumor Grading From Histopathology Images (original) (raw)

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