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Exploring a novel method for face image gender Classification using Random Forest and comparing with other Machine Learning Techniques
BibTeX
@MISC{Basha_exploringa,
author = {Amjath Fareeth Basha and Gul Shaira and Banu Jahangeer},
title = {Exploring a novel method for face image gender Classification using Random Forest and comparing with other Machine Learning Techniques},
year = {}
}
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Abstract
Gender classification such as classifying human face is not only challenging for computer, but even hard for human in some cases. This Paper use ORL database contain 400 images include both Male and Female Gender. Our experimental results show the superior performance of our approach to the existing gender classifiers. We achieves excellent classification (100%) accuracy using approach (Continuous wavelet Transform and Random Forest) and compared with other classification Technique like Support Vector Machine, linear discriminate analysis, k- nearest neighbor, Fuzzy c – means, Fuzzy c – means.
Keyphrases
random forest face image gender classification novel method machine learning technique fuzzy mean classification technique support vector machine continuous wavelet transform superior performance excellent classification linear discriminate analysis female gender paper use orl database contain gender classification experimental result human face gender classifier
