BIOLOGICALLY PLAUSIBLE ILLUSIONARY CONTRAST PERCEPTION WITH SPIKING NEURAL NETWORKS

Hadar Cohen-Duwek; Elishai Ezra Tsur

doi:10.1109/ICIP46576.2022.9897264

BIOLOGICALLY PLAUSIBLE ILLUSIONARY CONTRAST PERCEPTION WITH SPIKING NEURAL NETWORKS

Hadar Cohen-Duwek, Elishai Ezra Tsur

Computer Science discipline

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Illusionary visual perception has been long used to shed light on biological vision pathways and mechanisms. In this work, we propose a biologically plausible spiking neural network with which spike events are used for iterative image reconstruction in which illusionary contrast perception, long known to manifest in human vision, is apparent. This parametric implementation allows us to examine this visual phenomenon in a biologically plausible computational framework, which may also account for differences in individual visual perception.

Original language	English
Title of host publication	2022 IEEE International Conference on Image Processing, ICIP 2022 - Proceedings
Publisher	IEEE Computer Society
Pages	1586-1590
Number of pages	5
ISBN (Electronic)	9781665496209
DOIs	https://doi.org/10.1109/ICIP46576.2022.9897264
State	Published - 2022
Event	29th IEEE International Conference on Image Processing, ICIP 2022 - Bordeaux, France Duration: 16 Oct 2022 → 19 Oct 2022

Publication series

Name	Proceedings - International Conference on Image Processing, ICIP
ISSN (Print)	1522-4880

Conference

Conference	29th IEEE International Conference on Image Processing, ICIP 2022
Country/Territory	France
City	Bordeaux
Period	16/10/22 → 19/10/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

computational cognition
image reconstruction
neural engineering framework
visual illusions
visual perception

Access to Document

10.1109/ICIP46576.2022.9897264

Cite this

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title = "BIOLOGICALLY PLAUSIBLE ILLUSIONARY CONTRAST PERCEPTION WITH SPIKING NEURAL NETWORKS",

abstract = "Illusionary visual perception has been long used to shed light on biological vision pathways and mechanisms. In this work, we propose a biologically plausible spiking neural network with which spike events are used for iterative image reconstruction in which illusionary contrast perception, long known to manifest in human vision, is apparent. This parametric implementation allows us to examine this visual phenomenon in a biologically plausible computational framework, which may also account for differences in individual visual perception.",

keywords = "computational cognition, image reconstruction, neural engineering framework, visual illusions, visual perception",

author = "Hadar Cohen-Duwek and Tsur, {Elishai Ezra}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 29th IEEE International Conference on Image Processing, ICIP 2022 ; Conference date: 16-10-2022 Through 19-10-2022",

year = "2022",

doi = "10.1109/ICIP46576.2022.9897264",

language = "אנגלית",

series = "Proceedings - International Conference on Image Processing, ICIP",

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Cohen-Duwek, H & Tsur, EE 2022, BIOLOGICALLY PLAUSIBLE ILLUSIONARY CONTRAST PERCEPTION WITH SPIKING NEURAL NETWORKS. in 2022 IEEE International Conference on Image Processing, ICIP 2022 - Proceedings. Proceedings - International Conference on Image Processing, ICIP, IEEE Computer Society, pp. 1586-1590, 29th IEEE International Conference on Image Processing, ICIP 2022, Bordeaux, France, 16/10/22. https://doi.org/10.1109/ICIP46576.2022.9897264

BIOLOGICALLY PLAUSIBLE ILLUSIONARY CONTRAST PERCEPTION WITH SPIKING NEURAL NETWORKS. / Cohen-Duwek, Hadar; Tsur, Elishai Ezra.
2022 IEEE International Conference on Image Processing, ICIP 2022 - Proceedings. IEEE Computer Society, 2022. p. 1586-1590 (Proceedings - International Conference on Image Processing, ICIP).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Illusionary visual perception has been long used to shed light on biological vision pathways and mechanisms. In this work, we propose a biologically plausible spiking neural network with which spike events are used for iterative image reconstruction in which illusionary contrast perception, long known to manifest in human vision, is apparent. This parametric implementation allows us to examine this visual phenomenon in a biologically plausible computational framework, which may also account for differences in individual visual perception.

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BIOLOGICALLY PLAUSIBLE ILLUSIONARY CONTRAST PERCEPTION WITH SPIKING NEURAL NETWORKS

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