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Machine Learning Techniques for Image Recognition Applications

机译:图像识别应用的机器学习技术

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In the present paper is presented an algorithm to detect sleepiness of the driver. The purpose of this system is to locate, track and analyze face and eyes to prevent falling asleep, or the inattention of the driver working under different lighting conditions and, more importantly, in real time. Real-time processing is an absolute condition for the proper functioning of this system. The image acquisition is achieved with the help of a web camera, which is positioned on the dashboard of the car. For the face recognition task was used the support vector machine models. This is an artificial intelligence technique applied in the field of artificial vision, which is part of the supervised learning techniques.
机译:在本文中提出了一种检测驾驶员困倦的算法。该系统的目的是定位,跟踪和分析面部和眼睛,以防止入睡,或防止驾驶员在不同的照明条件下工作,更重要的是实时工作。实时处理是该系统正常运行的绝对条件。借助网络摄像头可以实现图像采集,该摄像头位于汽车的仪表板上。对于面部识别任务,使用支持向量机模型。这是一种应用于人工视觉领域的人工智能技术,是有监督学习技术的一部分。

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