%0 Journal Article
	%A Svitov David and  Alyamkin Sergey
	%D 2021
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 171, 2021
	%T MarginDistillation: Distillation for Face Recognition Neural Networks with Margin-Based Softmax
	%U https://publications.waset.org/pdf/10011902
	%V 171
	%X The usage of convolutional neural networks (CNNs) in
conjunction with the margin-based softmax approach demonstrates
the state-of-the-art performance for the face recognition problem.
Recently, lightweight neural network models trained with the
margin-based softmax have been introduced for the face identification
task for edge devices. In this paper, we propose a distillation method
for lightweight neural network architectures that outperforms other
known methods for the face recognition task on LFW, AgeDB-30
and Megaface datasets. The idea of the proposed method is to use
class centers from the teacher network for the student network. Then
the student network is trained to get the same angles between the
class centers and face embeddings predicted by the teacher network.
	%P 206 - 210