Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders.

Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders.

Recent neuroscience studies demonstrate that a deeper understanding of brain function requires a deeper understanding of behavior. Detailed behavioral measurements are now often collected using video cameras, resulting in an increased need for computer vision algorithms that extract useful informati...

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Autores principales: Matthew R Whiteway, Dan Biderman, Yoni Friedman, Mario Dipoppa, E Kelly Buchanan, Anqi Wu, John Zhou, Niccolò Bonacchi, Nathaniel J Miska, Jean-Paul Noel, Erica Rodriguez, Michael Schartner, Karolina Socha, Anne E Urai, C Daniel Salzman, International Brain Laboratory, John P Cunningham, Liam Paninski
Formato: article
Lenguaje:EN
Publicado: Public Library of Science (PLoS) 2021
Materias:
Biology (General)
QH301-705.5
Acceso en línea:https://doaj.org/article/8c044a2fffaa489890ca5e3b6a6b6664
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https://doaj.org/article/8c044a2fffaa489890ca5e3b6a6b6664

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