Profound impact of artificial neural networks and Gaussian SVM kernel on distinctive feature set for offline signature verification

2012 International Conference on Informatics, Electronics and Vision, ICIEV 2012

Volumn , Issue , 2012, Pages 940-945

  Miskhat, Sheikh Faisal ^a   Ridwan, Mahmud ^a   Chowdhury, Ehtesham ^a   Rahman, Saami ^a   Amin, M Ashraful ^b  

^a NORTH SOUTH UNIVERSITY   (Bangladesh)

^b INDEPENDENT UNIVERSITY   (Bangladesh)

Author keywords

ANN; distinctive features; dot density; feedforward backpropagation; Gaussian RBF kernel; gradient histograms; perceptron; polynomial kernel; slices; SVM

Indexed keywords

ANN; DISTINCTIVE FEATURES; DOT DENSITY; FEEDFORWARD BACKPROPAGATION; GRADIENT HISTOGRAMS; PERCEPTRON; POLYNOMIAL KERNELS; RBF KERNELS; SLICES; SVM;

GAUSSIAN DISTRIBUTION; GRAPHIC METHODS; INFORMATION SCIENCE; NEURAL NETWORKS; STATISTICAL METHODS;

SUPPORT VECTOR MACHINES;

EID: 84869458858     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIEV.2012.6317439     Document Type: Conference Paper

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