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. (Contributor), Roig Noguera, Gemma (Contributor), Isik, Leyla (Contributor), Boix Bosch, Xavier (Contributor), Poggio, Tomaso A (Contributor)
Other Authors: Center for Brains, Minds, and Machines (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Association for the Advancement of Artificial Intelligence, 2017-11-22T16:03:27Z.
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