首页> 外国专利> Learning method and learning device for sensor fusion to integrate information acquired by radar capable of distance estimation and information acquired by camera to thereby improve neural network for supporting autonomous driving, and testing method and testing device using the same

Learning method and learning device for sensor fusion to integrate information acquired by radar capable of distance estimation and information acquired by camera to thereby improve neural network for supporting autonomous driving, and testing method and testing device using the same

机译:传感器融合的学习方法和学习装置,用于融合能够进行距离估计的雷达获得的信息和相机获得的信息,从而改善用于支持自动驾驶的神经网络,以及使用该方法的测试方法和测试装置

摘要

A method for training a CNN by using a camera and a radar together, to thereby allow the CNN to perform properly even when an object depiction ratio of a photographed image acquired through the camera is low due to a bad condition of a photographing circumstance is provided. And the method includes steps of: (a) a learning device instructing a convolutional layer to apply a convolutional operation to a multichannel integrated image, to thereby generate a feature map; (b) the learning device instructing an output layer to apply an output operation to the feature map, to thereby generate estimated object information; and (c) the learning device instructing a loss layer to generate a loss by using the estimated object information and GT object information corresponding thereto, and to perform backpropagation by using the loss, to thereby learn at least part of parameters in the CNN.
机译:提供一种用于通过一起使用照相机和雷达来训练CNN,从而即使在由于摄影环境的不良条件而通过照相机获取的摄影图像的物体描绘率较低的情况下,也能够使CNN正常执行的方法。 。并且该方法包括以下步骤:(a)学习设备,指示卷积层将卷积运算应用于多通道集成图像,从而生成特征图;以及(b)学习设备指示输出层对特征图进行输出操作,从而生成估计的对象信息; (c)学习装置指示损失层通过使用估计的对象信息和与其对应的GT对象信息来产生损失,并通过使用该损失进行反向传播,从而学习CNN中的至少一部分参数。

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