人脸识别中的最近邻回归

Shu Yang, Chao Zhang
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引用次数: 5

摘要

在本文中,我们引入了一种用于一般分类任务的回归最近邻框架。为了缓解非线性带来的潜在问题,我们提出了核回归最近邻算法(KRNN)和其凸对偶算法(CKRNN)作为最近邻算法的两种具体扩展,并相应地提出了一种快速实用的核选择方法。综合分析和大量实验证明了我们的方法在真实人脸数据集上的有效性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Regression Nearest Neighbor in Face Recognition
In this paper, we introduce a regression nearest neighbor framework for general classification tasks. To alleviate potential problems caused by nonlinearity, we propose a kernel regression nearest neighbor (KRNN) algorithm and its convex counterpart (CKRNN) as two specific extensions of nearest neighbor algorithm and present a fast and useful kernel selection method correspondingly. Comprehensive analysis and extensive experiments are used to demonstrate the effectiveness of our methods in real face datasets
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