Research on face recognition algorithm based on multi task deep learning

Hainie Meng, Yunli Cheng
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引用次数: 1

Abstract

With the vigorous development of the new generation of information technology, deep learning technology based on big data has gradually become one of the mainstream technologies in the field of artificial intelligence. Face recognition is an important topic in the field of artificial intelligence and biometrics.It is widely used in business, security, identity authentication and many other aspects, and has become a dynamic research field.With the continuous improvement of application requirements, face recognition technology is no longer only for face identification, face attribute recognition is becoming more and more important.Firstly, a simplified multi task face recognition model is proposed and designed to speed up the operation;Secondly, the correlation among multiple learning tasks is used to improve the recognition accuracy of the model;After model training and selection, an end-to-end multi task face recognition model is obtained.The multi task face recognition algorithm can be fast and accurate in a short time, which can be widely used in intelligent driving behavior analysis, intelligent navigation and other fields.
基于多任务深度学习的人脸识别算法研究
随着新一代信息技术的蓬勃发展,基于大数据的深度学习技术逐渐成为人工智能领域的主流技术之一。人脸识别是人工智能和生物识别领域的一个重要课题。它广泛应用于商业、安全、身份认证等诸多方面,已成为一个充满活力的研究领域。随着应用需求的不断提高,人脸识别技术不再仅仅用于人脸识别,人脸属性识别变得越来越重要。首先,提出并设计了一种简化的多任务人脸识别模型,提高了操作速度;其次,利用多个学习任务之间的相关性提高了模型的识别精度;经过模型训练和选择,得到了端到端的多任务人脸识别模型。多任务人脸识别算法在短时间内快速准确,可广泛应用于智能驾驶行为分析、智能导航等领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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