What is the best multi-stage architecture for object recognition?

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2009, Pages 2146-2153

  Jarrett, Kevin ^a   Kavukcuoglu, Koray ^a   Ranzato, Marc'Aurelio ^a   LeCun, Yann ^a  

^a NEW YORK UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CALTECH; DATA SETS; ERROR RATE; LOCAL CONTRAST; MULTI-STAGE; NON-LINEAR TRANSFORMATIONS; NONLINEARITIES; OBJECT RECOGNITION SYSTEMS; PRE-TRAINING; RECOGNITION ACCURACY; RECOGNITION RATES; STATE-OF-THE-ART PERFORMANCE; TWO STAGE; TWO-STAGE SYSTEMS;

COMPUTER VISION; EXTRACTION; FILTER BANKS; LINEAR TRANSFORMATIONS; OBJECT RECOGNITION; TELEPHONE SYSTEMS;

FEATURE EXTRACTION;

EID: 77953183471     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2009.5459469     Document Type: Conference Paper

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