Described is a system for online vehicle recognition in an autonomous driving environment. Using a learning network comprising an unsupervised learning component and a supervised learning component, images of moving vehicles extracted from videos captured in the autonomous driving environment are learned and classified. Vehicle feature data is extracted from input moving vehicle images. The extracted vehicle feature data is clustered into different vehicle classes using the unsupervised learning component. Vehicle class labels for the different vehicle classes are generated using the supervised learning component. Based on a vehicle class label for a moving vehicle in the autonomous driving environment, the system selects an action to be performed by the autonomous vehicle, and causes theselected action to be performed by the autonomous vehicle in the autonomous driving environment.
描述了一种用于自主驾驶环境中的在线车辆识别的系统。使用包括无监督学习部件和有监督学习部件的学习网络,对从在自主驾驶环境中拍摄的视频提取的移动车辆图像进行学习和分类。从输入的移动车辆图像提取车辆特征数据。使用无监督学习部件将所提取的车辆特征数据聚类成不同车辆类别。使用有监督学习部件来生成不同车辆类别的车辆类别标记。基于自主驾驶环境中的移动车辆的车辆类别标记,所述系统选择将由自主车辆执行的动作,并使该自主车辆在自主驾驶环境中执行所选择的动作。
METHOD OF REAL TIME VEHICLE RECOGNITION WITH NEUROMORPHIC COMPUTING NETWORK FOR AUTONOMOUS DRIVING
利用用于自主驾驶的神经形态计算网络进行实时车辆识别的方法
2021-02-19
Patent
Elektronische Ressource
Chinesisch
IPC: | B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen |
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