afr

Automatic Face Recognition ( AFR ) is challenging in image processing and analyzing.

自动人脸识别技术 ( AFR ) 是一项极具挑战性的前沿研究课题.

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In addition, elaborate system design is also as important for developing robust and practical AFR systems.

另外,对开发鲁棒实用的AFR系统 而言, 研究应用系统设计层面的诸多工程技术问题同样至关重要.

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In this thesis, the above - mentioned key issues are studied , aiming at robust and practical AFR systems.

以设计开发鲁棒、实用的AFR系统为目标,本文重点探讨了人脸识别中的上述关键问题.

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Model based AFR control strategy requires accurate engine model first.

基于模型的空燃比控制策略首先要求有精确的模型,均值模型是非线性模型,其精度高、表达形式简单,能够满足控制过程实时性的要求,是比较理想的模型.

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Based on the traditional eigenfaces method, this paper presents an improving approach to AFR.

在传统的“特征脸”方法基础上, 提出了一种改进的人脸自动识别方法.

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However, evaluation results and practical experience have shown that AFR technologies are currently far from mature.

但测试和实践经验表明:非理想条件下的人脸识别技术还远未成熟!

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