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.
CONVOLUTIONAL NEURAL NETWORK SYSTEM FOR OBJECT DETECTION AND LANE DETECTION IN A MOTOR VEHICLE
2020-09-10
Patent
Electronic Resource
English
IPC: | B60R Fahrzeuge, Fahrzeugausstattung oder Fahrzeugteile, soweit nicht anderweitig vorgesehen , VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G06V |
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