Exploiting sparse representations in very high-dimensional feature spaces obtained from patch-based processing

Machine Vision and Applications

Volumn 22, Issue 3, 2011, Pages 449-460

  Hunter, J E ^a   Tugcu, M ^a   Wang, X ^a   Costello, C ^a   Wilkes, D M ^a  

^a VANDERBILT UNIVERSITY   (United States)

Author keywords

High dimensional feature space; Machine learning; Object recognition; Scene recognition

Indexed keywords

APPROXIMATE NEAREST NEIGHBOR; CALCULATION COST; COLOR SPACE; FEATURE SPACE; FEATURE VECTORS; HIGH-DIMENSIONAL; HIGH-DIMENSIONAL FEATURE SPACE; IMAGE PATCHES; MACHINE-LEARNING; MIXED METRICS; SCENE RECOGNITION; SPARSE REPRESENTATION; SPARSE VECTORS; STANDARD PROBLEMS; TRAINING REQUIREMENT; TREE STRUCTURES;

OBJECT RECOGNITION; PLANT EXTRACTS; STRUCTURAL OPTIMIZATION; TREES (MATHEMATICS);

FEATURE EXTRACTION;

EID: 79958849492     PISSN: 09328092     EISSN: 14321769     Source Type: Journal    
DOI: 10.1007/s00138-010-0263-2     Document Type: Article

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