English

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

Computer Vision and Pattern Recognition 2021-01-28 v1 Artificial Intelligence

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.

Keywords

Cite

@article{arxiv.2101.11266,
  title  = {TorchPRISM: Principal Image Sections Mapping, a novel method for Convolutional Neural Network features visualization},
  author = {Tomasz Szandala},
  journal= {arXiv preprint arXiv:2101.11266},
  year   = {2021}
}

Comments

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

R2 v1 2026-06-23T22:34:33.482Z