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Nonlinear Discrete Cross-Modal Hashing for Visual-Textual Data
Dekui Ma1; Jian Liang2; Ran He2; Xiangwei Kong3
Source PublicationIEEE MULTIMEDIA
AbstractDiscrete cross-modal hashing is a supervised method that exploits classification tasks to learn heterogeneous binary codes. DCMH also updates the binary codes for each modality and learns discrete hashing codes bit by bit, making it promising for large-scale datasets.
KeywordCross-modal Hashing Multi-media
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
Funding OrganizationNational Natural Science Foundation of China(61502073 ; Foundation for Innovative Research Groups of the NSFC(71421001) ; Open Projects Program of National Laboratory of Pattern Recognition(201407349) ; Strategic Priority Research Program of the Chinese Academy of Sciences(XDB02070000) ; 61473289)
WOS Research AreaComputer Science
WOS SubjectComputer Science, Hardware & Architecture ; Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods
WOS IDWOS:000401288300008
Citation statistics
Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Dalian Univ Technol, Sch Informat & Commun, Dalian, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
3.Dalian Univ Technol, Sch Informat & Commun Engn, Dalian, Peoples R China
Recommended Citation
GB/T 7714
Dekui Ma,Jian Liang,Ran He,et al. Nonlinear Discrete Cross-Modal Hashing for Visual-Textual Data[J]. IEEE MULTIMEDIA,2017,24(2):56-65.
APA Dekui Ma,Jian Liang,Ran He,&Xiangwei Kong.(2017).Nonlinear Discrete Cross-Modal Hashing for Visual-Textual Data.IEEE MULTIMEDIA,24(2),56-65.
MLA Dekui Ma,et al."Nonlinear Discrete Cross-Modal Hashing for Visual-Textual Data".IEEE MULTIMEDIA 24.2(2017):56-65.
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