New Deep Learning Model for Face Recognition and Registration in Distance Learning
Yazarlar (2)
Ahmed B. Salem Salamh
Kastamonu Üniversitesi
Kastamonu Üniversitesi
Doç. Dr. Halil İbrahim AKYÜZ Kastamonu Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(ESCI dergilerinde yayınlanan tam makale)
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| Dergi Adı | INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING | ||
| Dergi ISSN | 1863-0383 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | ESCI | ||
| Makale Dili | Türkçe | Basım Tarihi | 01-2022 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 21-06-2022 |
| Cilt / Sayı / Sayfa | 17 / 12 / 29–41 | DOI | 10.3991/ijet.v17i12.30377 |
| Makale Linki | https://online-journals.org/index.php/i-jet/article/view/30377/11491 | ||
| UAK Araştırma Alanları |
Bilişim Teknolojileri Eğitimi
Eğitim Teknolojileri
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| 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 … |
| Anahtar Kelimeler |
| Deep learning | Distance learning | Face identification | Face recognition | Feature extraction |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 7 |
| Google Scholar | 16 |