A tale of two classifiers: SNoW vs. SVM in visual recognition

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2353, Issue , 2002, Pages 685-699

  Yang, Ming Hsuan ^a   Roth, Dan ^b   Ahuja, Narendra ^b  

^a HONDA RESEARCH INSTITUTE   (United States)

^b University of Illinois at Urbana Champaign   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATION THEORY; COMPUTER VISION; LEARNING ALGORITHMS; LEARNING SYSTEMS; OBJECT DETECTION; OBJECT RECOGNITION; SNOW;

COMPUTATIONAL LEARNING THEORY; DETECTION EXPERIMENTS; GENERALIZATION BOUND; LARGE MARGIN CLASSIFIERS; OBJECT DETECTION AND RECOGNITION; ROBUSTNESS PROPERTIES; STATISTICAL LEARNING METHODS; VISUAL RECOGNITION;

FACE RECOGNITION;

EID: 84937539670     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-47979-1_46     Document Type: Conference Paper

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