On random hyper-class random forest for visual classification

Neurocomputing

Volumn 172, Issue , 2016, Pages 281-289

  Li, Teng ^a   Ni, Bingbing ^b   Wu, Xinyu ^c   Gao, Qingwei ^a   Li, Qianmu ^d   Sun, Dong ^a  

^a ANHUI UNIVERSITY   (China)

^b ADVANCED DIGITAL SCIENCES CENTER   (Singapore)

^c SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY   (China)

^d NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Binary splitting; Multiple attributes; Random forest; Random hyper class; Visual classification

Indexed keywords

CHARACTER RECOGNITION; CLASSIFICATION (OF INFORMATION); DECISION TREES; FACE RECOGNITION; FORESTRY; OPTICAL CHARACTER RECOGNITION; PATTERN RECOGNITION; RANDOM PROCESSES;

BINARY SPLITTING; MULTIPLE ATTRIBUTES; RANDOM FORESTS; RANDOM HYPER-CLASS; VISUAL CLASSIFICATION;

IMAGE CLASSIFICATION;

ACCURACY; ARTICLE; CALCULATION; DATA ANALYSIS; IMAGE ANALYSIS; IMAGE PROCESSING; INFORMATION PROCESSING; MATHEMATICAL COMPUTING; PRIORITY JOURNAL; PROCESS DEVELOPMENT; PROCESS OPTIMIZATION; RANDOM FOREST; VISUAL CLASSIFICATION;

EID: 84946496249     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2014.10.101     Document Type: Article

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