A light-weight Gender/Age Estimation model based on Multi-taking Deep Learning for an Embedded System

임베디드 시스템을 위한 멀티태스킹 딥러닝 학습 기반 경량화 성별/연령별 추정

Age estimation and gender classification for human is a classic problem in computer vision. Almost research focus just only one task and the models are too heavy to run on low-cost system. In our research, we aim to apply multitasking learning to perform both task on a lightweight model which can achieve good precision on embedded system in the real time.