Papers › TorchPRISM: Principal Image Sections Mapping, a novel method for Convolutional Neural...
TorchPRISM: Principal Image Sections Mapping, a novel method for Convolutional Neural Network features visualization
Tomasz Szandala
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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