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New Deep Learning Model for Face Recognition and Registration in Distance Learning    
Yazarlar
Ahmed B. Salem Salamh
Doç. Dr. Halil İbrahim AKYÜZ
Kastamonu Üniversitesi, Türkiye
Özet
The demand for secure, accurate and reliable identification of individuals using facial recognition has attracted considerable interest in education, security and many other sectors, not limited because it is robust, secure and authentic. Recently, the demand for distance learning has increased dramatically. This increase is due to various barriers to learning that arise from enforced conditions such as seclusion and social distancing. Facial feature extraction in distance education is valuable in supporting face authenticity as it prevents the position of participants from changing, especially during the examination phase. In the field of face recognition, there is a mismatch between research and practical application. In this paper, we present a novel but highly efficient Deep Learning model for improving face recognition and registration in distance education. The technique is based on a combination of sequential and residual identity blocking. This makes it possible to evaluate the effectiveness of using deeper blocks than other models. The new model has proven to be able to extract features from faces in a high and accurate manner in compared with other state-of-the-art methods. In registration processing, there are several challenges related to training data limitation, face recognition and verification. We present a new architecture for face recognition and registration. Experiments have shown that our registration model is capable of recognizing almost all faces and registering the corresponding labels.
Anahtar Kelimeler
face recognition,deep learning,face identification,distance learning,feature extraction
Makale Türü Özgün Makale
Makale Alt Türü ESCI dergilerinde yayımlanan tam makale
Dergi Adı International Journal of Emerging Technologies in Learning (iJET)
Dergi ISSN 1863-0383
Dergi Tarandığı Indeksler ESCI
Makale Dili Türkçe
Basım Tarihi 06-2022
Cilt No 17
Sayı 12
Sayfalar 29 / 41
Doi Numarası 10.3991/ijet.v17i12.30377
Makale Linki https://online-journals.org/index.php/i-jet/article/view/30377/11491