Eccentricity dependent deep neural networks: Modeling invariance in human vision

Eccentricity dependent deep neural networks: Modeling invariance in human vision

Humans can recognize objects in a way that is invariant to scale, translation, and clutter. We use invariance theory as a conceptual basis, to computationally model this phenomenon. This theory discusses the role of eccentricity in human visual processing, and is a generalization of feedforward conv...

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Bibliographic Details
Main Authors: Chen, Francis X., Roig Noguera, Gemma, Isik, Leyla, Boix Bosch, Xavier, Poggio, Tomaso A
Other Authors: Center for Brains, Minds, and Machines
Format: Article
Published: Association for the Advancement of Artificial Intelligence 2017
Online Access:http://hdl.handle.net/1721.1/112279
https://orcid.org/0000-0002-1909-257X
https://orcid.org/0000-0002-7470-0179
https://orcid.org/0000-0002-9255-0151
https://orcid.org/0000-0002-3944-0455

Internet

http://hdl.handle.net/1721.1/112279
https://orcid.org/0000-0002-1909-257X
https://orcid.org/0000-0002-7470-0179
https://orcid.org/0000-0002-9255-0151
https://orcid.org/0000-0002-3944-0455

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