ArticleFrontiers in computational neuroscience2018
Perceptual Dominance in Brief Presentations of Mixed Images: Human Perception vs. Deep Neural Networks.
Article in Frontiers in computational neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Article
- ImageNet-trained deep neural networks exhibit illusion-like response to the Scintillating grid.Journal of vision · 2021Article
- Oculo-retinal dynamics can explain the perception of minimal recognizable configurations.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Convergent evolution of face spaces across human face-selective neuronal groups and deep convolutional networks.Nature communications · 2019Article
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Authors and funding
4 authors.
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Abstract
Visual perception involves continuously choosing the most prominent inputs while suppressing others. Neuroscientists induce visual competitions in various ways to study why and how the brain makes choices of what to perceive. Recently deep neural networks (DNNs) have been used as models of the ventral stream of the visual system, due to similarities in both accuracy and hierarchy of feature representation. In this study we created non-dynamic visual competitions for humans by briefly presenting mixtures of two images. We then tested feed-forward DNNs with similar mixtures and examined their behavior. We found that both humans and DNNs tend to perceive only one image when presented with a mixture of two. We revealed image parameters which predict this perceptual dominance and compared their predictability for the two visual systems. Our findings can be used to both improve DNNs as models, as well as potentially improve their performance by imitating biological behaviors.
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