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K-Means Clustering-Based Approach for Face Recognition

机译:基于K均值聚类的人脸识别方法

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In recent years, computer-based automatic face recognition technology has been widely concerned. At present, the majority of face recognition systems are using supervised machine learning techniques. These systems require a training step to learn a model for human face recognition task. This paper uses the face recognition method which is based on non-supervised learning to realize a non-supervised Face Recognition System. In this system, non-supervised k-means clustering algorithm replaces the classification algorithm used in the previous face recognition system. Finally, the proposed method was tested by the standard test and the experiments show that under certain conditions the system has a high recognition rate.
机译:近年来,基于计算机的自动面部识别技术已受到广泛关注。目前,大多数人脸识别系统正在使用监督式机器学习技术。这些系统需要训练步骤才能学习人脸识别任务的模型。本文采用基于非监督学习的人脸识别方法,实现了非监督人脸识别系统。在该系统中,非监督k均值聚类算法取代了先前的人脸识别系统中使用的分类算法。最后,通过标准测试对提出的方法进行了测试,实验表明该方法在一定条件下具有较高的识别率。

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