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首页> 外文期刊>Artificial Intelligence Review: An International Science and Engineering Journal >A unified framework for improving the accuracy of all holistic face identification algorithms Electoral College for human face identification by computing machinery
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A unified framework for improving the accuracy of all holistic face identification algorithms Electoral College for human face identification by computing machinery

机译:一个提高所有整体人脸识别算法准确性的统一框架选举学院通过计算机器进行人脸识别

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摘要

Reconstructing the challenging human face identification process as a stability problem, we show that Electoral College can be used as a framework that provides a significantly enhanced face identification process by improving the accuracy of all holistic algorithms. The results are demonstrated by extensive experiments on benchmark face databases applying the Electoral College framework embedded with standard baseline and newly developed face identification algorithms.
机译:将具有挑战性的人脸识别过程重构为一个稳定性问题,我们表明选举学院可以用作通过提高所有整体算法的准确性来显着增强人脸识别过程的框架。通过使用嵌入标准基线和新开发的人脸识别算法的选举学院框架在基准人脸数据库上进行的大量实验证明了结果。

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