The ART2 Neural Network Based on the Adaboost Rough Classification
The ART2 Neural Network Based on the Adaboost Rough Classification
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DOI：
10.1007/978-3-642-37149-3_6
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发表时间：
2013-04
期刊：
影响因子：
--
通讯作者：
Mingming Wang;Mingming Wang;Xiaozhu Lin
中科院分区：
文献类型：
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作者：
Mingming Wang;Mingming Wang;Xiaozhu Lin
在人脸识别的应用中，随着ART2网络中存储的人脸模式越来越多，它将花费大量的时间来学习或识别ART2网络的未来进入模式，然后人脸识别的速度就会变慢。作者提出了一种基于粗糙分类的改进ART2算法，利用adaboost算法训练一个分类器来判断人脸是否戴眼镜，人脸模式将人脸分为戴眼镜的人和不戴眼镜的人，通过决定一个人是否戴眼镜。实验表明，该方法可以大大提高人脸识别的速度。
In the application of face recognition, with the increasing number of stored face mode in ART2 network, it will spend a lot of time to learn or identify the future entering mode of ART2 network, and then the speed of face recognition will become slower. The author proposed an improved ART2 algorithm based on rough classification, using the adaboost algorithm to train a classifier to determine whether the face wearing glasses, the face mode will be divided into two categories of people who wear glasses and do not wear glasses by deciding a people whether to wear glasses. The experiments show that the method can greatly improve the speed of face recognition.