TorchPRISM: Principal Image Sections Mapping, a novel method for Convolutional Neural Network features visualization

Abstract

In this paper we introduce a tool called Principal Image Sections Mapping - PRISM, dedicated for PyTorch, but can be easily ported to other deep learning frameworks. Presented software relies on Principal Component Analysis to visualize the most significant features recognized by a given Convolutional Neural Network. Moreover, it allows to display comparative set features between images processed in the same batch, therefore PRISM can be a method well synerging with technique Explanation by Example.

Very early draft, software can be found: https://github.com/szandala/TorchPRISM