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

Tomasz Szandala

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arXiv · 2101.11266

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

Tomasz Szandala

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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.

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Tomasz Szandala. 2021-01-27. TorchPRISM: Principal Image Sections Mapping, a novel method for Convolutional Neural Network features visualization. https://arxiv.org/abs/2101.11266

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