Deep sparse feature selection for computer aided endoscopy diagnosis

Pattern Recognition

Volumn 48, Issue 3, 2015, Pages 907-917

  Cong, Yang ^a,b   Wang, Shuai ^a,e   Liu, Ji ^b   Cao, Jun ^c   Yang, Yunsheng ^d   Luo, Jiebo ^b  

^a SHENYANG INSTITUTE OF AUTOMATION   (China)

^b University of Rochester   (United States)

^c Arizona State University   (United States)

^d CHINESE PLA GENERAL HOSPITAL   (China)

^e UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

Author keywords

Computer aided diagnosis; Deep sparse; Endoscopy; Feature selection; Group sparsity; Image representation

Indexed keywords

COMPUTER AIDED DIAGNOSIS; ENDOSCOPY; IMAGE SEGMENTATION; KNOWLEDGE REPRESENTATION; SUPPORT VECTOR MACHINES; TEXTURES;

COLOR AND TEXTURE FEATURES; COMPUTATION COMPLEXITY; DEEP SPARSE; EFFECTIVENESS AND EFFICIENCIES; ENDOSCOPIC EXAMINATION; FEATURE DIMENSIONS; GROUP SPARSITIES; IMAGE REPRESENTATIONS;

FEATURE EXTRACTION;

EID: 84916882621     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2014.09.010     Document Type: Article

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