Visual recognition and inference using dynamic overcomplete sparse learning

We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and expectation-driven segmentation. Using properties of biological vision for guidance, we posit a stochastic generative worl...

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Vydané v:	Neural computation Ročník 19; číslo 9; s. 2301
Hlavní autori:	Murray, Joseph F, Kreutz-Delgado, Kenneth
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 01.09.2007
Predmet:	Algorithms Artificial Intelligence Humans Learning - physiology Models, Neurological Nonlinear Dynamics Pattern Recognition, Visual - physiology Photic Stimulation
ISSN:	0899-7667
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