Valliappan Raman1, Khaled ELKarazle2,*, Patrick Then2
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1341-1355, 2023, DOI:10.32604/csse.2023.026674
Abstract Given the current expansion of the computer vision field, several applications that rely on extracting biometric information like facial gender for access control, security or marketing purposes are becoming more common. A typical gender classifier requires many training samples to learn as many distinguishable features as possible. However, collecting facial images from individuals is usually a sensitive task, and it might violate either an individual's privacy or a specific data privacy law. In order to bridge the gap between privacy and the need for many facial images for deep learning training, an artificially generated dataset of facial images is proposed.… More >
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