Object detection via feature synthesis using MDL-based genetic programming

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 35, Issue 3, 2005, Pages 538-547

  Lin, Yingqiang ^a   Bhanu, Bir ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Feature learning; Minimum description length (MDL); Primitive feature image; Primitive operator; Synthetic aperture radar (SAR) image

Indexed keywords

FEATURE EXTRACTION; GENETIC ALGORITHMS; LEARNING SYSTEMS; RADAR IMAGING; SYNTHETIC APERTURE RADAR;

FEATURE LEARNING; MINIMUM DESCRIPTION LENGTH; PRIMITIVE FEATURE IMAGE; PRIMITIVE OPERATOR;

OBJECT RECOGNITION;

ALGORITHM; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; CLUSTER ANALYSIS; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; LETTER; MATHEMATICAL COMPUTING; METHODOLOGY; SIGNAL PROCESSING; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; MODELS, GENETIC; MODELS, STATISTICAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUBTRACTION TECHNIQUE;

EID: 20444411822     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2005.846656     Document Type: Article

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