Facial gender recognition, deferent approaches
Publish place: Scientific Journal of Review (SJR)، Vol: 4، Issue: 11
Publish Year: 1394
Type: Journal paper
Language: English
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JR_SJR-4-11_001
Index date: 26 February 2024
Facial gender recognition, deferent approaches abstract
Gender recognition is one of the most interesting problems in face processing. Gender recognition can be used as a preprocessing phase in many applications. In this work we compare different approaches for gender recognition task, in accuracy and generalizing. First we use principle component analysis (PCA) and discrete cosine transformation (DCT), for feature extraction and dimension reduction. Additionally we used Bayesian approach and support vector machine (SVM) too. Finally, we compare these approaches in accuracy and generalizing.Gender recognition is one of the most interesting problems in face processing. Gender recognition can be used as a preprocessing phase in many applications. In this work we compare different approaches for gender recognition task, in accuracy and generalizing. First we use principle component analysis (PCA) and discrete cosine transformation (DCT), for feature extraction and dimension reduction. Additionally we used Bayesian approach and support vector machine (SVM) too. Finally, we compare these approaches in accuracy and generalizing.
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Facial gender recognition, deferent approaches authors
F. Yaghmaee
Faculty of Electerical and Computer Engineering, Semnan, Iran
R. Khammari
Faculty of Electerical and Computer Engineering, Semnan, Iran
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