DocumentCode :
1949423
Title :
Gender classification using ANN based on human radiation frequencies
Author :
Haron, M.H. ; Taib, M.N. ; Megat Ali, M.S.A. ; Mohd Yunus, Megawati ; Jalil, Siti Zura A.
Author_Institution :
Fac. of Electr. Eng., Univ. Teknol. MARA, Shah Alam, Malaysia
fYear :
2012
fDate :
17-19 Dec. 2012
Firstpage :
610
Lastpage :
614
Abstract :
This paper discusses about classification of human gender based on human frequencies of chakra points and brain regions. The main techniques used in this study are Artificial Neural Network (ANN) and k-fold cross-validation. ANN technique has been used for gender prediction and k-fold cross-validation for validation of classifier. All measurements are based on radio frequency readings. Data from 34 samples consist of 17 males and 17 females have been recorded. Three groups of points have been analyzed during classification and validation. Group 1 consists of seven chakra points and four brain regions, Group 2 consists of three chakra points and Group 3 consists of three chakra points and one brain region. The results show the variables in Group 1 are best for gender classification.
Keywords :
biomedical measurement; brain; medical computing; neural nets; pattern classification; ANN technique; Artificial Neural Network; brain regions; chakra points; gender classification; gender prediction; human gender; human radiation frequencies; k-fold cross-validation; radio frequency reading measurements; Chakra; artificial neural network; brain regions; k-fold cross-validation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Sciences (IECBES), 2012 IEEE EMBS Conference on
Conference_Location :
Langkawi
Print_ISBN :
978-1-4673-1664-4
Type :
conf
DOI :
10.1109/IECBES.2012.6498041
Filename :
6498041
Link To Document :
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