Quantization-based hashing: a general framework for scalable image and video retrieval

Pattern Recognition

Volumn 75, Issue , 2018, Pages 1339-1351

  Song, Jingkuan ^a   Gao, Lianli ^a   Liu, Li ^b   Zhu, Xiaofeng ^c   Sebe, Nicu ^d  

^a UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b UNIVERSITY OF EAST ANGLIA   (United Kingdom)

^c GUANGXI NORMAL UNIVERSITY   (China)

^d UNIVERSITY OF TRENTO   (Italy)

Author keywords

Hashing; Multimedia retrieval; Pseudo labels

Indexed keywords

CODES (SYMBOLS); ERRORS; HAMMING DISTANCE; HASH FUNCTIONS; ITERATIVE METHODS; NETWORK FUNCTION VIRTUALIZATION; TABLE LOOKUP;

EXPONENTIAL GROWTH; FLEXIBLE DISTANCE; GENERIC FRAMEWORKS; HASHING; LABEL INFORMATION; MULTIMEDIA RETRIEVAL; PROPERTY-PRESERVING; QUANTIZATION ERRORS;

VECTOR QUANTIZATION;

EID: 85017230141     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2017.03.021     Document Type: Article

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