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Contextual effects, image statistics, and deep learning
mardi 07 décembre 2021

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Descriptif

Conférence de Odelia Schwartz (University of Miami) dans le cadre du Colloquium du département d'Etudes Cognitives de l'ENS-PSL.

Neural responses and perception of visual inputs strongly depend on the spatial context, i.e., what surrounds a given object or feature. I will discuss our work on developing a visual cortical model based on the hypothesis that neurons represent inputs in a coordinate system that is matched to the statistical structure of images in the natural environment. The model generalizes a nonlinear computation known as normalization, that is ubiquitous in neural processing, and can capture some spatial context effects in cortical neurons. I will further discuss how we are incorporating such nonlinearities into deep neural networks.

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Auteur(s)
Odelia Schwartz
University of Miami
Professeure

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Cursus :

Odelia Schwartz est professeure associée au département d'informatique de l'université de Miami. Ses recherches se situent à l'intersection des sciences du cerveau et de l'apprentissage automatique. Elle s'est principalement attachée à comprendre comment le cerveau donne un sens aux informations visuelles dans le monde.

Elle a obtenu un doctorat au Center for Neural Science de l'université de New York et un master en informatique à l'université de Floride. Elle a effectué ses recherches postdoctorales à l'Institut Salk. Ses recherches ont été financées par la NSF, le NIH, l'Army Research Office, une bourse de recherche de la faculté de Google et une bourse de recherche Alfred P. Sloan.

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Dernière mise à jour : 16/12/2021