Titlebook: Computer Vision for Driver Assistance; Simultaneous Traffic Mahdi Rezaei,Reinhard Klette Book 2017 Springer International Publishing AG 201

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Erratum to: Computer Vision for Driver Assistance: Simultaneous Traffic and Driver Monitoring,

Increment

The Demographic Correlates of Health Status,d information to reach a higher degree of certainty. The proposed algorithm is able to detect vehicles ahead both at day and night, and also for a wide range of distances. Experimental results under various conditions, including sunny, rainy, foggy, or snowy weather, show that the proposed algorithm

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opalescence

Vision-Based Driver-Assistance Systems,le at all times, but provided automated control features of the vehicle (based on input data generated by different sensors) already enhance safety and driver comfort. We especially consider automated control features possible by using camera data.

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爵士乐

Object Detection, Classification, and Tracking,ised and unsupervised learning approaches. The chapter provides technical details for each method, discussions on the strengths and weaknesses of each method, and gives examples and various applications for each method. Material is provided to support a decision for an appropriate object detection t

教育学

CANON

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