A new approach for automatic recognition of melanoma in profilometry - Optimized feature selection using genetic algorithms

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 3338, Issue , 1998, Pages 684-692

  Handels, Heinz ^a   Ross Th ^a   Kreusch, J ^a   Wolff, H H ^a   Poppl S J ^a  

^a UNIVERSITY OF LÜBECK   (Germany)

Author keywords

Genetic algorithms; Image analysis; Melanoma; Neural networks; Pattern recognition; Profilometry

Indexed keywords

CLASSIFIERS; GENETIC ALGORITHMS; HEURISTIC ALGORITHMS; IMAGE ANALYSIS; IMAGING SYSTEMS; LEARNING SYSTEMS; MEDICAL IMAGING; NEURAL NETWORKS; PATTERN RECOGNITION; PROFILOMETRY; THICKNESS MEASUREMENT;

AUTOMATIC RECOGNITION; CLASSIFICATION PERFORMANCE; ERROR BACK PROPAGATION; ERROR RATES; FEATURE SELECTION PROBLEMS; FEATURE SELECTIONS; FEATURE SUBSETS; FEED-FORWARD NEURAL NETWORKS; FOURIER; FRACTAL ANALYSIS; GREEDY ALGORITHMS; HEURISTIC STRATEGIES; HIGH RESOLUTIONS; IMAGE ANALYSIS ALGORITHMS; LASER PROFILOMETER; LEARNING PARAMETERS; MELANOMA; NEAREST NEIGHBOR CLASSIFIERS; NETWORK PRUNING; NEURAL CLASSIFIERS; NEW APPROACHES; PRUNING ALGORITHMS; QUALITY MEASURES; SAMPLE POINTS; SKIN SURFACES; VERTICAL RESOLUTIONS;

LEARNING ALGORITHMS;

EID: 0345388031     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.310948     Document Type: Conference Paper

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