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大数据生物特征识别技术研究进展 被引量:2

Research progress and trend of big-data based biometrics
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摘要 随着机器学习领域研究的持续发展,特别是深度学习方面的进步及图像处理器(GPU)等算力的持续提高,利用生物特征大数据的识别技术获得广泛关注,并在人证比对、智能监控以及疫情防控等多个领域取得了很好的应用。分析了大数据生物特征识别技术的发展态势,总结了生物特征类型以及大数据驱动的生物特征识别技术发展与应用,探讨了大数据生物特征识别技术的未来发展趋势。 Biometric recognition refers to the use of inherent physiological or behavioral characteristics of human body for personal identification,such as face recognition,fingerprint recognition,and iris recognition.Early technologies are usually based on handcrafted features and traditional machine learning methods,and constrained by data and computing power acquisition ability.Thus,they are generally limited to controlled environment and difficult to build powerful biometric recognition models by making use of large-scale biometric data effectively.In recent years,with the advancement of machine learning,especially deep learning and increasing computing power of GPU,big data based biometric recognition technologies have received widespread attention and have been widely used in the areas such as personal authentication,intelligent video surveillance,and prevention and control of epidemic.This paper summarizes the development of big-data based biometrics technologies,covering different types of biometrics and their applications,and then discusses the trend of big-data based biometrics technologies in the future.
作者 刘琦 于汉超 蔡剑成 韩琥 LIU Qi;YU Hanchao;CAI Jiancheng;HAN Hu(Henan Police College,Zhengzhou 450000,China;Bureau of Frontier Sciences and Education,Chinese Academy of Sciences,Beijing 100864,China;Pengcheng National Laboratory,Shenzhen 518055,China)
出处 《科技导报》 CAS CSCD 北大核心 2021年第19期74-82,共9页 Science & Technology Review
基金 国家自然科学基金项目(61732004,62176249)。
关键词 生物特征识别 大数据驱动 自监督学习 领域通用特征 人工智能 biometric recognition big data driven self-supervised learning universal domain representation artificial intelligence
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