S. Michael Dinesh1,*, A. R. Kavitha2
Computer Systems Science and Engineering, Vol.44, No.1, pp. 545-561, 2023, DOI:10.32604/csse.2023.024450
Abstract Deep learning has risen in popularity as a face recognition technology in recent years. Facenet, a deep convolutional neural network (DCNN) developed by Google, recognizes faces with 128 bytes per face. It also claims to have achieved 99.96% on the reputed Labelled Faces in the Wild (LFW) dataset. However, the accuracy and validation rate of Facenet drops down eventually, there is a gradual decrease in the resolution of the images. This research paper aims at developing a new facial recognition system that can produce a higher accuracy rate and validation rate on low-resolution face images. The proposed system Extended Openface… More >
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