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

TL;DR

TorchPRISM is a visualization tool for CNN features that uses PCA to highlight significant features and enables comparison between images, aiding interpretability of deep learning models.

Contribution

Introduces PRISM, a PCA-based visualization tool for CNNs that supports feature comparison and can be integrated with explanation techniques.

Findings

Effective visualization of CNN features using PCA.

Supports comparative analysis of image features.

Eases interpretation of deep neural network decisions.

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.