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Research on face recognition algorithm based on multi task deep learning

机译：基于多任务深度学习的人脸识别算法研究

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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.
机译：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。人工智能和生物识别领域的人物识别是一个重要的主题。它广泛用于商业，安全性，身份认证和许多其他方面，并已成为一种动态研究领域。在持续改进应用要求，人脸识别技术不再用于面部识别，面部属性识别正变得越来越重要。首先，提出了一种简化的多任务面部识别模型，旨在加速操作;其次，使用多个学习任务之间的相关性来改善识别模型的准确性;在模型训练和选择之后，获得了端到端的多任务面部识别模型。多任务面部识别算法在短时间内可以快速准确，可以广泛用于智能驾驶行为分析，智能导航和其他字段。

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