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|a eng
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| 100 |
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|a Serre, Thomas
|e verfasserin
|4 aut
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|a Robust object recognition with cortex-like mechanisms
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|c 2007
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|a Text
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|a ohne Hilfsmittel zu benutzen
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|a Date Completed 27.03.2007
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|a Date Revised 08.04.2022
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|a published: Print
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|a Citation Status MEDLINE
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|a We introduce a new general framework for the recognition of complex visual scenes, which is motivated by biology: We describe a hierarchical system that closely follows the organization of visual cortex and builds an increasingly complex and invariant feature representation by alternating between a template matching and a maximum pooling operation. We demonstrate the strength of the approach on a range of recognition tasks: From invariant single object recognition in clutter to multiclass categorization problems and complex scene understanding tasks that rely on the recognition of both shape-based as well as texture-based objects. Given the biological constraints that the system had to satisfy, the approach performs surprisingly well: It has the capability of learning from only a few training examples and competes with state-of-the-art systems. We also discuss the existence of a universal, redundant dictionary of features that could handle the recognition of most object categories. In addition to its relevance for computer vision, the success of this approach suggests a plausibility proof for a class of feedforward models of object recognition in cortex
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|a Evaluation Study
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|a Research Support, U.S. Gov't, Non-P.H.S.
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| 700 |
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|a Wolf, Lior
|e verfasserin
|4 aut
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| 700 |
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|a Bileschi, Stanley
|e verfasserin
|4 aut
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| 700 |
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|a Riesenhuber, Maximilian
|e verfasserin
|4 aut
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| 700 |
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|a Poggio, Tomaso
|e verfasserin
|4 aut
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 29(2007), 3 vom: 16. März, Seite 411-26
|w (DE-627)NLM098212257
|x 1939-3539
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|g volume:29
|g year:2007
|g number:3
|g day:16
|g month:03
|g pages:411-26
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