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Recently, face recognition algorithms have made great progress in various real-world applications, e.g., authentication and criminal investigation. Deep-learning offers an end-to-end paradigm for vision recognition tasks and achieves good performance. However, designing and training the complex network architecture are time-consuming and labor-intensive. Moreover, under complex scenarios, illumination...
Recently, deep learning based face recognition algorithms have achieved great success in recognition performance. However, designing and training complex learning models suffer from time and labor efficiency. In this paper, we propose a novel three-layer low-rank supported extreme learning machine (LSELM) algorithm to take advantage of both robust feature representation and fast classification for...
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