基于人脸大数据人工智能聚类的自适应识别系统

Hui Du
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引用次数: 1

摘要

随着大数据相关领域的发展,人脸识别的研究取得了很大的进展。然而,复杂的外部不确定因素仍然是影响人脸识别系统性能的关键问题之一。因此,如何解决不确定变化对人脸识别性能的影响已成为实际人脸识别技术中的一个具有挑战性的问题。本文以复杂不确定因素下的人脸识别问题为主要研究对象,着重对人工智能算法和聚类特征提取算法进行了深入研究,并提出了相应的自适应识别系统方案:基于改进的图形人脸识别算法和基于人工智能聚类的特征融合人脸识别算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive recognition system based on human face big data artificial intelligence clustering
With the development of big data related fields, the research of face recognition has made great progress. However, complex external uncertain factors are still one of the key issues affecting the performance of face recognition systems. Therefore, how to solve the impact of uncertain changes on the performance of face recognition has become a challenging problem in practical face recognition technology. This paper takes the face recognition problem under complex uncertain factors as the main research object, focuses on the in-depth study of artificial intelligence algorithms and clustering feature extraction algorithms, and proposes a corresponding adaptive recognition system scheme: based on improved graph face recognition algorithm And feature fusion face recognition algorithm based on artificial intelligence clustering.
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