2026-09-21T05:58:12Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/6187 2021-12-13T05:08:22Z 1582963342780:1596102355557 user-uit

Child Face Recognition System Using Mobilefacenet Shun Lei Myat Oo Aung Nway Oo Face recognition is a kind of identifying people in image. It matches the database of known faces and input image of unknown face. Deep learning is one of the state-of-art technologies which achieve state-of-art performance on face recognition. In this paper, we develop child face recognition using MobileFaceNet. MobileFaceNet is efficient Convolutional Neural Network (CNN) models and it uses more than 1 million parameters. MobileFaceNet is used for feature extractions. Since MobileFaceNet is one of the types of light weights models, we can apply this face recognition system on mobile and embedded devices. Dlib is used for preprocessing and K-Nearest Neighbors (KNN) is used for classification process. MobileFaceNet is trained by ArcFace loss and it achieve the 96% accuracy on child face dataset. 2019-09-02 http://hdl.handle.net/20.500.12678/0000006187 https://meral.edu.mm/records/6187