mlsanityData to 14 Oct 2026

How Do ConvNets Understand Image Intensity?

arXiv 2306.00360 ↗First posted 1 Jun 2023cs.CV cs.LGcited by 0

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Abstract (arXiv)

Convolutional Neural Networks (ConvNets) usually rely on edge/shape information to classify images. Visualization methods developed over the last decade confirm that ConvNets rely on edge information. We investigate situations where the ConvNet needs to rely on image intensity in addition to shape. We show that the ConvNet relies on image intensity information using visualization.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 11 references that are in the map. First posted on arXiv 1 Jun 2023.

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4 of 11 references.

References · 4

  1. 2013Visualizing and Understanding Convolutional Networkscited by 2,290
  2. 2018Sanity Checks for Saliency Mapscited by 1,156
  3. 2014Striving for Simplicity: The All Convolutional Netcited by 990
  4. 2023Automatic Photo Orientation Detection with Convolutional Neural Networkscited by 4

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