Facial gender recognition is an important and attractive research topic due to its extensive use cases, including gender demographic scanning, targeted advertising, access control, and visitor profile identification. The framework of the proposed method for face detection face consists of Adaboost, Integral Image, Haar- features, and Cascade Classifier. The LFW dataset containing 13,233 facial images was used.
Hassan,B AbedRuda and Dawood,F Abd Ali. (2023). Facial image detection based on the Viola-Jones algorithm for gender recognition. International Journal of Nonlinear Analysis and Applications, 14(1), 1593-1599. doi: 10.22075/ijnaa.2022.7130
MLA
Hassan,B AbedRuda, and Dawood,F Abd Ali. "Facial image detection based on the Viola-Jones algorithm for gender recognition", International Journal of Nonlinear Analysis and Applications, 14, 1, 2023, 1593-1599. doi: 10.22075/ijnaa.2022.7130
HARVARD
Hassan B AbedRuda, Dawood F Abd Ali. (2023). 'Facial image detection based on the Viola-Jones algorithm for gender recognition', International Journal of Nonlinear Analysis and Applications, 14(1), pp. 1593-1599. doi: 10.22075/ijnaa.2022.7130
CHICAGO
B AbedRuda Hassan and F Abd Ali Dawood, "Facial image detection based on the Viola-Jones algorithm for gender recognition," International Journal of Nonlinear Analysis and Applications, 14 1 (2023): 1593-1599, doi: 10.22075/ijnaa.2022.7130
VANCOUVER
Hassan B AbedRuda, Dawood F Abd Ali. Facial image detection based on the Viola-Jones algorithm for gender recognition. IJNAA. 2023;14(1):1593-1599. doi: 10.22075/ijnaa.2022.7130
International Journal of Nonlinear Analysis and Applications