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FACE DETECTION USING ARTIFICIAL NEURAL NETWORK APPROACH

机译:使用人工神经网络方法进行脸部检测

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A frontal face detection system using artificial neural network is presented The system used integral image for image representation which allows fast computation of the features used The system also applies the AdaBoost learning algorithm to select a small number of critical visual features from a very large set of potential features. Besides that, it also used cascade of classifiers algorithm which allows background regions of the image to be quickly discarded while spending more computation on promising face-like regions. Furthermore, a set of experiments in the domain of face detection is presented The system yields a promising face detection performance.
机译:使用人工神经网络的正面检测系统呈现了用于图像表示的系统使用的积分图像,其允许快速计算使用的功能,该系统也应用Adaboost学习算法从一组中选择少量的临界视觉功能潜在的功能。除此之外,它还使用级联分类器算法,该算法允许图像的背景区域快速丢弃,同时在承诺的面部地区花费更多的计算。此外,介绍了面部检测领域的一组实验,该系统产生了有希望的面部检测性能。

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