首页> 外国专利> LEARNING METHOD AND LEARNING DEVICE FOR INTEGRATING OBJECT DETECTION INFORMATION ACQUIRED THROUGH V2V COMMUNICATION FROM OTHER AUTONOMOUS VEHICLE WITH OBJECT DETECTION INFORMATION GENERATED BY PRESENT AUTONOMOUS VEHICLE, AND TESTING METHOD AND TESTING DEVICE USING THE SAME

LEARNING METHOD AND LEARNING DEVICE FOR INTEGRATING OBJECT DETECTION INFORMATION ACQUIRED THROUGH V2V COMMUNICATION FROM OTHER AUTONOMOUS VEHICLE WITH OBJECT DETECTION INFORMATION GENERATED BY PRESENT AUTONOMOUS VEHICLE, AND TESTING METHOD AND TESTING DEVICE USING THE SAME

机译:用于将通过其他自主车辆的V2V通信获得的对象检测信息与当前自主车辆生成的对象检测信息集成在一起的学习方法和学习装置,以及使用该方法进行检测的设备

摘要

A learning method for generating integrated object detection information by integrating first object detection information and second object detection information is provided. And the method includes steps of: (a) a learning device instructing a concatenating network to generate one or more pair feature vectors; (b) the learning device instructing a determining network to apply FC operations to the pair feature vectors, to thereby generate (i) determination vectors and (ii) box regression vectors; (c) the learning device instructing a loss unit to generate an integrated loss by referring to the determination vectors, the box regression vectors and their corresponding GTs, and performing backpropagation processes by using the integrated loss, to thereby learn at least part of parameters included in the DNN.
机译:提供一种用于通过整合第一物体检测信息和第二物体检测信息来生成整合物体检测信息的学习方法。并且该方法包括以下步骤:(a)学习装置指示级联网络生成一个或多个对特征向量; (b)学习设备指示确定网络将FC操作应用于对特征向量,从而生成(i)确定向量和(ii)盒回归向量; (c)学习装置通过参考确定向量,箱回归向量及其对应的GT来指示损失单元生成累积损失,并利用该累积损失执行反向传播处理,从而学习至少包括的参数的一部分在DNN中。

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