Zobrazeno 1 - 7 of 7 pro vyhledávání: '"Lynn Schmittwilken"'
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Akademický článek
Capsule networks as recurrent models of grouping and segmentation.
Autor: Adrien Doerig, Lynn Schmittwilken, Bilge Sayim, Mauro Manassi, Michael H Herzog
Publikováno v: PLoS Computational Biology, Vol 16, Iss 7, p e1008017 (2020)
Classically, visual processing is described as a cascade of local feedforward computations. Feedforward Convolutional Neural Networks (ffCNNs) have shown how powerful such models can be. However, using visual crowding as a well-controlled challenge,
Externí odkaz: https://doaj.org/article/e1153922e55d44b68c7e24339459fdb3
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3
Fixational eye movements enable robust edge detection
Autor: Lynn Schmittwilken, Marianne Maertens
Publikováno v: Journal of vision. 22(8)
Human vision relies on mechanisms that respond to luminance edges in space and time. Most edge models use orientation-selective mechanisms on multiple spatial scales and operate on static inputs assuming that edge processing occurs within a single fi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70f6f6b979f75cdedc58013549ff3840
https://pubmed.ncbi.nlm.nih.gov/35834376
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5
How crowding challenges (feedforward) convolutional neural networks
Autor: Adrien Doerig, Gregory Francis, Lynn Schmittwilken, Alban Bornet, Michael H. Herzog, Ben Lonnqvist
Publikováno v: Journal of Vision, 21, 9, pp. 2039
Journal of Vision, 21, 2039
Item does not contain fulltext Are (feedforward) convolutional neural networks (CNNs) good models for the human visual system? Here, we used visual crowding as a well-controlled psychophysical test to probe CNNs. Visual crowding is a ubiquitous break
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::670a88b7dafde9961d27845426efdf68
https://doi.org/10.1167/jov.21.9.2039
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