TY - GEN
T1 - ARTriViT
T2 - 32nd IEEE International Symposium on Industrial Electronics, ISIE 2023
AU - Khan, Mustaqeem
AU - Saeed, Muhammad
AU - El Saddik, Abdulmotaleb
AU - Gueaieb, Wail
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Computer-based face recognition and other biometric techniques are now mature and trustworthy technology that plays a crucial role in many access control scenarios. Face recognition undergoes a variety of difficulties, including those related to angle, lighting, position, facial expression, noise, resolution, occlusion, and the scarcity of samples from each class. In this study, we proposed a triplet loss-based Siamese network with a vision transformer as a feature extractor instead of traditional convolution. Our Siamese analyzes a pair of face images as input, extracts the characteristics from these pairs, and uses similarity indexes to evaluate them for face recognition using the Celeb-DF (version 2) dataset. As a result, the suggested model performs well compared to the state-of-the-art (SOTA) on the Celeb-DF version 2 dataset. The trained model and code will be available at: https://github.com/MuhammadSaeedMBZUAINiTBased-Siamese.
AB - Computer-based face recognition and other biometric techniques are now mature and trustworthy technology that plays a crucial role in many access control scenarios. Face recognition undergoes a variety of difficulties, including those related to angle, lighting, position, facial expression, noise, resolution, occlusion, and the scarcity of samples from each class. In this study, we proposed a triplet loss-based Siamese network with a vision transformer as a feature extractor instead of traditional convolution. Our Siamese analyzes a pair of face images as input, extracts the characteristics from these pairs, and uses similarity indexes to evaluate them for face recognition using the Celeb-DF (version 2) dataset. As a result, the suggested model performs well compared to the state-of-the-art (SOTA) on the Celeb-DF version 2 dataset. The trained model and code will be available at: https://github.com/MuhammadSaeedMBZUAINiTBased-Siamese.
KW - Face Recognition
KW - Siamese Neural Network
KW - Triplet Loss
KW - Vision Transformers
UR - http://www.scopus.com/inward/record.url?scp=85172083591&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85172083591&partnerID=8YFLogxK
U2 - 10.1109/ISIE51358.2023.10228106
DO - 10.1109/ISIE51358.2023.10228106
M3 - Conference contribution
AN - SCOPUS:85172083591
T3 - IEEE International Symposium on Industrial Electronics
BT - 2023 IEEE 32nd International Symposium on Industrial Electronics, ISIE 2023 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 19 June 2023 through 21 June 2023
ER -