首页> 外国专利> A learning method and learning device that updates the HD map by reconstructing the 3D space using the depth prediction information for each object and the class information for each object acquired by the V2X information fusion technology, and using this. Testing method and testing equipment

A learning method and learning device that updates the HD map by reconstructing the 3D space using the depth prediction information for each object and the class information for each object acquired by the V2X information fusion technology, and using this. Testing method and testing equipment

机译:一种学习方法和学习设备,可以通过使用每个对象的深度预测信息和由V2X信息融合技术获取的每个对象的广泛预测信息来重建3D空间来更新HD映射的学习设备,以及用于由V2X信息融合技术获取的每个对象的类信息。测试方法和测试设备

摘要

PROBLEM TO BE SOLVED: To provide a method for rebuilding a 3D space and updating a HD map.;SOLUTION: The present invention includes: a step in which a learning device causes a coordinate neural network 130 to generate a local feature map and a global feature vector applying coordinate neural network computation to a coordinate matrix; a step in which the learning device causes a determination neural network 140 to generate a first or an N-th prediction suitability score map applying determination neural network computation to an integrated feature map; and a step in which the learning device causes a loss layer to generate a loss referring to the first prediction suitability score or the N-th prediction suitability score and a first GT suitability score or the N-th GT suitability score and carry out back propagation utilizing the loss, thereby learning parameters of the determination and coordinate neural networks.;SELECTED DRAWING: Figure 3;COPYRIGHT: (C)2020,JPO&INPIT
机译:要解决的问题:提供一种重建3D空间的方法并更新高清映射。;解决方案:本发明包括:学习设备使坐标神经网络130生成本地特征映射和全局的步骤特征向量应用坐标神经网络计算到坐标矩阵;学习设备使确定神经网络140生成第一或第n预测适用性评分将确定神经网络计算的第一或第n预测适用性评分映射到集成特征映射的步骤;并且学习设备导致丢失层产生损耗的步骤,以产生第一预测适用性得分或第n个预测适用性评分和第n个GT适用性得分或第n个GT适合性评分并进行反向传播利用损失,从而学习确定和坐标神经网络的参数。;所选绘图:图3;版权:(c)2020,JPO和INPIT

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