论文标题
使用高斯接受场扩展类激活映射
Extending Class Activation Mapping Using Gaussian Receptive Field
论文作者
论文摘要
本文讨论了深度学习模型的可视化任务。为了改善基于类激活映射（CAM）的可视化方法，我们提供了两个选项。首先，我们提出了高斯上升采样，这是一种改进的上采样方法，可以反映深度学习模型的特征。其次，我们在现有CAM研究的数学推导中识别并修改了不自然的术语。基于两个选项，我们提出了扩展-CAM，这是一种基于CAM的高级可视化方法，该方法具有改善的理论特性。实验结果表明，扩展-CAM比现有方法提供了更准确的可视化。
This paper addresses the visualization task of deep learning models. To improve Class Activation Mapping (CAM) based visualization method, we offer two options. First, we propose Gaussian upsampling, an improved upsampling method that can reflect the characteristics of deep learning models. Second, we identify and modify unnatural terms in the mathematical derivation of the existing CAM studies. Based on two options, we propose Extended-CAM, an advanced CAM-based visualization method, which exhibits improved theoretical properties. Experimental results show that Extended-CAM provides more accurate visualization than the existing methods.
