LogDet divergence-based metric learning with triplet constraints and its applications

IEEE Transactions on Image Processing

Volumn 23, Issue 11, 2014, Pages 4920-4931

  Mei, Jiangyuan ^a   Liu, Meizhu ^c   Karimi, Hamid Reza ^d   Gao, Huijun ^a,b  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b KING ABDULAZIZ UNIVERSITY   (Saudi Arabia)

^c YAHOO RESEARCH   (United States)

^d UNIVERSITY OF AGDER   (Norway)

Author keywords

compressed representation; high dimensional data; LogDet divergence; metric learning; triplet constraint

Indexed keywords

COMPRESSED REPRESENTATION; HIGH DIMENSIONAL DATA; LOGDET DIVERGENCE; METRIC LEARNING; TRIPLET CONSTRAINT;

ALGORITHM; ANATOMY AND HISTOLOGY; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOMETRY; COMPUTER ASSISTED DIAGNOSIS; FACE; FACIAL EXPRESSION; HUMAN; IMAGE ENHANCEMENT; PHOTOGRAPHY; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOMETRY; DATA INTERPRETATION, STATISTICAL; FACE; FACIAL EXPRESSION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; PHOTOGRAPHY; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84908108461     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2014.2359765     Document Type: Article

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