
The author presents T-TAME as a general methodology for explaining deep neural networks used in image classification tasks, demonstrating its effectiveness over existing state-of-the-art explainability methods. The approach involves a trainable attention mechanism compatible with both CNN and ViT backbones.


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t-tame-trainable-attention-mechanism-for-explaining-convolutional-networks-and-vision-transformers


T-TAME: Trainable Attention Mechanism for Explaining Convolutional Networks and Vision Transformers


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T-TAMEは、画像分類タスクで使用される深層ニューラルネットワークを説明するための汎用的な方法論を提供します。
