Facial gender recognition, deferent approaches
Journal Title: Scientific Journal of Review - Year 2015, Vol 4, Issue 11
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.
Authors and Affiliations
F. Yaghmaee*| Faculty of Electerical and Computer Engineering, Semnan, Iran., R. Khammari| Faculty of Electerical and Computer Engineering, Semnan, Iran.
Keywords
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- EP ID EP217
- DOI 10.14196/sjr.v4i11.2055
- Views 461
- Downloads 40
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