The effect of low-level image features on pseudo relevance feedback

Neurocomputing

Volumn 166, Issue , 2015, Pages 26-37

  Lin, Wei Chao ^a   Chen, Zong Yao ^b   Ke, Shih Wen ^c   Tsai, Chih Fong ^b   Lin, Wei Yang ^d  

^a HWA HSIA INSTITUTE OF TECHNOLOGY   (Taiwan)

^b NATIONAL CENTRAL UNIVERSITY   (Taiwan)

^c CHUNG YUAN CHRISTIAN UNIVERSITY   (Taiwan)

^d NATIONAL CHUNG CHENG UNIVERSITY   (Taiwan)

Author keywords

Feature representation; Image retrieval; Pseudo relevance feedback; Relevance feedback; Rocchio algorithm

Indexed keywords

CONTENT BASED RETRIEVAL; IMAGE ENHANCEMENT; IMAGE RETRIEVAL; TEXTURES;

CONTENT BASED IMAGE RETRIEVAL SYSTEMS; FEATURE REPRESENTATION; IMAGE FEATURE REPRESENTATION; LOW-LEVEL IMAGE FEATURES; PSEUDO RELEVANCE FEEDBACK; PSEUDO-RELEVANCE FEEDBACKS; RELEVANCE FEEDBACK; ROCCHIO ALGORITHM;

SEARCH ENGINES;

ALGORITHM; ARTICLE; AUTOMATION; CALCULATION; CONTROLLED STUDY; FEEDBACK SYSTEM; IMAGE ANALYSIS; IMAGE DISPLAY; INFORMATION RETRIEVAL; LINEAR SYSTEM; MATHEMATICAL COMPUTING; MEASUREMENT PRECISION; PRIORITY JOURNAL; PSEUDO RELEVANCE FEEDBACK; RESPONSE TIME; ROCCHIO ALGORITHM; WAVELET ANALYSIS;

EID: 84931568327     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2015.04.037     Document Type: Article

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