Models of object recognition.

M Riesenhuber; T Poggio

doi:10.1038/81479

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PubMed · 11127838

Models of object recognition.

M Riesenhuber·T Poggio

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Abstract

Understanding how biological visual systems recognize objects is one of the ultimate goals in computational neuroscience. From the computational viewpoint of learning, different recognition tasks, such as categorization and identification, are similar, representing different trade-offs between specificity and invariance. Thus, the different tasks do not require different classes of models. We briefly review some recent trends in computational vision and then focus on feedforward, view-based models that are supported by psychophysical and physiological data.

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Animals Humans Learning Models, Neurological Nerve Net Neurons Pattern Recognition, Visual Temporal Lobe Visual Cortex Visual Pathways Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.Review

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M Riesenhuber, T Poggio. 2000. Models of object recognition.. https://doi.org/10.1038/81479

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