  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.
