afr

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

自動人臉識別技術 ( AFR ) 是一項極具挑戰性的前沿研究課題.

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

另外,對開發魯棒實用的AFR系統 而言, 研究應用系統設計層面的諸多工程技術問題同樣至關重要.

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

以設計開發魯棒、實用的AFR系統為目標,本文重點探討了人臉識別中的上述關鍵問題.

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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確的模型,均值模型是非線性模型,其精度高、表達形式簡單,能夠滿足控制過程實時性的要求,是比較理想的模型.

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

在傳統的“特征臉”方法基礎上, 提出了一種改進的人臉自動識別方法.

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

但測試和實踐經驗表明:非理想條件下的人臉識別技術還遠未成熟!

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