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Cloud Based Big Data Analytics Framework for Face Recognition in Social Networks Using Machine Learning

机译:基于云的大数据分析框架,用于使用机器学习的社交网络中的人脸识别

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Face recognition (FR) has been at the crux of several novel breakthroughs over the past two decades and has steadily proffered several cross-domain applications that range from mainstream commercial software to critical law enforcement applications. Recent groundbreaking developments in Big Data analysis , Cloud Computing , Social Networks and Machine learning have vastly transformed the conventional view of how several formidable problems in Computer Vision can be tackled. Hence in this paper, we will provide a thorough survey of the concepts of Cloud Computing, Big Data, Social networks and Machine Learning from a contemporary perspective of FR,and proffer a framework for a novel FR approachbased on the Extreme Learning Machines technique to perform the task of Face Tagging for Social Networks operating on Big Data. In the proposed approach, the desirable properties of the aforementioned concepts are amalgamated to form an effective coalition that can augment the performance of FR, in addition to serving immeasurably in a plethora of other disciplines.
机译:在过去的二十年中,人脸识别(FR)一直是数个新颖突破的关键,并且稳步提供了几种跨域应用程序,从主流商业软件到关键的执法应用程序不等。大数据分析,云计算,社交网络和机器学习方面的最新突破性发展已极大地改变了传统的观点,即如何解决计算机视觉中的若干难题。因此,在本文中,我们将从当代FR的角度对云计算,大数据,社交网络和机器学习的概念进行全面的调查,并提供一种基于极限学习机器技术的新颖FR方法的框架来执行在大数据上运行的社交网络的人脸标记任务。在提出的方法中,将上述概念的理想属性进行合并,以形成一个有效的联盟,该联盟可以在众多其他学科中发挥不可估量的作用,而且可以增强FR的性能。

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