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0001427.pdf
Preview of https://www.eurasip. org/Proceedings/Eusi pco/Eusipco2020/pdfs /0001427.pdf
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📊 Size: 2.27 MB
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Summary

Neural network models are used in various applications, but their decisions are often nontransparent. This study proposes techniques to determine which input image of a Multi-View Fusion Neural Network (MVFNN) has the most influence on the prediction of the model for a particular image sample pair and which regions in the input images are important. The study uses Grad-CAM and masked image inputs to analyze the influence of multiple image inputs on the prediction score of a particular class. The results show that the studied model learned similar concepts like a human, and the proposed method can be used to quantify which input has the most influence on the prediction score.

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Description

Neural network models are used in various applications, but their decisions are often nontransparent.

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  • File Format: PDF
  • File Size: 2.27 MB
  • Pages: 5
  • Language: EN
  • Total Downloads: 233
  • Last Updated: 3 hours ago

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