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Jun, 2022
FD-CAM:CNN视觉解释的保真性和可辨别性改进
FD-CAM: Improving Faithfulness and Discriminability of Visual Explanation for CNNs
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Hui Li, Zihao Li, Rui Ma, Tieru Wu
TL;DR
本文提出了一种新的CAM加权方案FD-CAM,它结合了改进的基于分数和传统基于梯度的权重计算,通过分组通道切换操作和改进的分数权重计算来提高权重的准确性,可以更好地解释CNN模型的输出。
Abstract
class activation map
(CAM) has been widely studied for visual explanation of the internal working mechanism of
convolutional neural networks
. The key of existing CAM-based methods is to compute effective weights
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