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A METHOD OF REAL TIME VEHICLE RECOGNITION WITH NEUROMORPHIC COMPUTING NETWORK FOR AUTONOMOUS DRIVING

机译：一种基于神经网络的实时驾驶车辆自动驾驶识别方法

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摘要

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 the selected action to be performed by the autonomous vehicle in the autonomous driving environment.

机译：描述了一种用于在自动驾驶环境中在线车辆识别的系统。使用包括无监督学习组件和有监督学习组件的学习网络，学习并分类从在自动驾驶环境中捕获的视频中提取的运动车辆的图像。从输入的运动车辆图像中提取车辆特征数据。使用无监督学习组件将提取的车辆特征数据聚类为不同的车辆类别。使用监督学习组件生成不同车辆类别的车辆类别标签。基于自动驾驶环境中的移动车辆的车辆类别标签，系统选择将由自动驾驶车辆执行的动作，并使所选动作由自动驾驶车辆在自动驾驶环境中执行。

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公开/公告号WO2020023518A1

专利类型
公开/公告日2020-01-30

原文格式PDF
申请/专利权人 HRL LABORATORIES LLC;
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申请/专利号WO2019US43051
发明设计人 JIANG QIN;CHO YOUNGKWAN;STEPP NIGEL D.;SKORHEIM STEVEN W.;DE SAPIO VINCENT;PILLY PRAVEEN K.;RUGGERO SCORCIONI;
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申请日2019-07-23
分类号B60W30/14;B60W40/02;G06N3/08;
国家 WO
入库时间 2022-08-21 11:13:39

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