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CONVOLUTIONAL NEURAL NETWORK SYSTEM FOR OBJECT DETECTION AND LANE DETECTION IN A MOTOR VEHICLE
CONVOLUTIONAL NEURAL NETWORK SYSTEM FOR OBJECT DETECTION AND LANE DETECTION IN A MOTOR VEHICLE
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机译：用于车辆目标检测和车道检测的卷积神经网络系统
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摘要
A system and method for predicting object detection and lane detection for a motor vehicle includes a convolution neural network (CNN) that receives an input image and a lane line module. The CNN includes a set of convolution and pooling layers (CPL's) trained to detect objects and lane markings from the input image, the objects categorized into object classes and the lane markings categorized into lane marking classes to generate a number of feature maps, a fully connected layer that receives the feature maps, the fully connected layer generating multiple object bounding box predictions for each of the object classes and multiple lane bounding box predictions for each of the lane marking classes from the feature maps, and a non-maximum suppression layer generating a final object bounding box prediction for each of the object classes and generating multiple final lane bounding box predictions for each of the lane marking classes.
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