An image retrieval scheme with relevance feedback using feature reconstruction and SVM reclassification

Neurocomputing

Volumn 127, Issue , 2014, Pages 214-230

  Wang, Xiang Yang ^a,b   Li, Yong Wei ^a   Yang, Hong Ying ^a   Chen, Jing Wei ^a  

^a LIAONING NORMAL UNIVERSITY   (China)

^b NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Content based image retrieval; Feature reconstruction; Orthogonal complement component analysis; Relevance feedback; Support vector machine

Indexed keywords

COMPONENT ANALYSIS; CONTENT BASED IMAGE RETRIEVAL; FEATURE RECONSTRUCTION; HIGH LEVEL SEMANTICS; HIGH-DIMENSIONAL FEATURE SPACE; ORTHOGONAL COMPLEMENTS; RELEVANCE FEEDBACK; STATE-OF-THE-ART APPROACH;

ALGORITHMS; CLASSIFICATION (OF INFORMATION); CONTENT BASED RETRIEVAL; COVARIANCE MATRIX; IMAGE RECONSTRUCTION; NONLINEAR ANALYSIS; SUPPORT VECTOR MACHINES;

FEEDBACK;

ALGORITHM; ARTICLE; COVARIANCE; DATA BASE; FEEDBACK SYSTEM; IMAGE RECONSTRUCTION; IMAGE RETRIEVAL; IMAGING SYSTEM; KERNEL METHOD; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; NEGATIVE FEEDBACK; NONLINEAR SYSTEM; POSITIVE FEEDBACK; PRIORITY JOURNAL; STATISTICAL ANALYSIS; SUPPORT VECTOR MACHINE;

EID: 84888432294     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2013.08.007     Document Type: Article

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