Efficient learning of sparse, distributed, convolutional feature representations for object recognition

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2011, Pages 2643-2650

  Sohn, Kihyuk ^a   Jung, Dae Yon ^a   Lee, Honglak ^a   Hero, Alfred O ^a  

^a UNIVERSITY OF MICHIGAN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CALTECH; CLASSIFICATION PERFORMANCE; DATA SETS; EFFICIENT LEARNING; EXPRESSIVE POWER; FEATURE REPRESENTATION; GAUSSIAN MIXTURE MODEL; HYPER-PARAMETER; IMAGE REPRESENTATIONS; MIXTURE MODEL; RESTRICTED BOLTZMANN MACHINE; SPATIAL CONTEXT; STATE-OF-THE-ART PERFORMANCE; TRAINING METHODS;

CONVOLUTION; LEARNING ALGORITHMS;

OBJECT RECOGNITION;

EID: 84863049755     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2011.6126554     Document Type: Conference Paper

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