Facial gender recognition, deferent approaches

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YAGHMAEE FARZIN; Khammari Reza

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Paper Information

Journal: SRPH JOURNAL OF INTERDISCIPLINARY STUDIES Year:2020 | Volume:2 | Issue:3 Page(s): 1-5

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Information Journal Paper

Title

Facial gender recognition, deferent approaches

Author(s)

YAGHMAEE FARZIN | Khammari Reza | Issue Writer Certificate

Keywords

facial gender recognition

SVM

DCT

PCA

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.

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APA: Copy

YAGHMAEE, FARZIN, & Khammari, Reza. (2020). Facial gender recognition, deferent approaches. SRPH JOURNAL OF INTERDISCIPLINARY STUDIES, 2(3 ), 1-5. SID. https://sid.ir/paper/404343/en

Vancouver: Copy

YAGHMAEE FARZIN, Khammari Reza. Facial gender recognition, deferent approaches. SRPH JOURNAL OF INTERDISCIPLINARY STUDIES[Internet]. 2020;2(3 ):1-5. Available from: https://sid.ir/paper/404343/en

IEEE: Copy

FARZIN YAGHMAEE, and Reza Khammari, “Facial gender recognition, deferent approaches,” SRPH JOURNAL OF INTERDISCIPLINARY STUDIES, vol. 2, no. 3 , pp. 1–5, 2020, [Online]. Available: https://sid.ir/paper/404343/en

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