Abednego Septian Primary Author mixed material bibliography Bandung ITB Journal Publisher 2021 e English

Artikel Jurnal

hlm : 251-264 Abstract Security systems must be continuously developed in order to cope with new challenges. One example of such challenges is the proliferation of sexual harassment against women in public places, such as public toilets and public transportation. Although separately designated toilets or waiting and seating areas in public transports are provided, enforcing these restrictions need constant manual surveillance. In this paper we propose an automatic gender classification system based on an individual?s facial characteristics. We evaluate the performance of QLRBP and MLLPQ as feature extractors combined with SVM or kNN as classifiers. Our experiments show that MLLPQ gives superior performance compared to QLRBP for either classifier. Furthermore, MLLPQ is less computationally demanding compared to QLRBP. The best result we achieved in our experiments was the combination of MLLPQ and kNN classifier, yielding an accuracy rate of 92.11%. Ilmu Teknik JICTRA 23375787 Perpustakaan Teknik UPI YAI JICTRA V15N3 December 2021 JICTRA6-004 Perpustakaan FT UPI YAI JICTRA V15N3 December 2021 JICTRA_ITB_small.png.png 59062 2023-02-15 16:56:12 2023-02-15 16:56:12 machine generated