A new automatic parameter setting method of a simplified PCNN for image segmentation

IEEE Transactions on Neural Networks

Volumn 22, Issue 6, 2011, Pages 880-892

  Chen, Yuli ^a,b   Park, Sung Kee ^b   Ma, Yide ^a   Ala, Rajeshkanna ^b  

^a LANZHOU UNIVERSITY   (China)

^b Korea Institute of Science and Technology   (South Korea)

Author keywords

Automatic parameter setting; dynamic property; general formulae; image segmentation; optimal histogram threshold; simplified pulse coupled neural network; standard deviation; static property; sub intensity range

Indexed keywords

DYNAMIC PROPERTY; GENERAL FORMULAE; OPTIMAL HISTOGRAM THRESHOLD; PARAMETER SETTING; SIMPLIFIED PULSE COUPLED NEURAL NETWORK; STANDARD DEVIATION; STATIC PROPERTY; SUB-INTENSITY RANGE;

GRAPHIC METHODS; NEURAL NETWORKS; OPTIMIZATION; STANDARDIZATION; STATISTICS;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; METHODOLOGY; THEORETICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED;

EID: 79957971391     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2011.2128880     Document Type: Article

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