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Systems and Methods for Training Predictive Models for Autonomous Devices

机译:用于自主设备训练预测模型的系统和方法

摘要

Systems and methods for training machine-learned models are provided. A method can include receiving a rasterized image associated with a training object and generating a predicted trajectory of the training object by inputting the rasterized image into a first machine-learned model. The method can include converting the predicted trajectory into a rasterized trajectory that spatially corresponds to the rasterized image. The method can include utilizing a second machine-learned model to determine an accuracy of the predicted trajectory based on the rasterized trajectory. The method can include determining an overall loss for the first machine-learned model based on the accuracy of the predictive trajectory as determined by the second machine-learned model. The method can include training the first machine-learned model by minimizing the overall loss for the first machine-learned model.
机译:提供了用于训练机器学习模型的系统和方法。方法可以包括接收与训练对象相关联的光栅化图像,并通过将光栅化图像输入到第一机器学习模型来生成训练对象的预测轨迹。该方法可以包括将预测的轨迹转换成在空间上对应于光栅化图像的光栅化轨迹中。该方法可以包括利用第二机器学习模型来基于光栅化轨迹来确定预测轨迹的准确性。该方法可以包括基于由第二机器学习模型确定的预测轨迹的准确性来确定第一机器学习模型的总损失。该方法可以包括通过最小化第一机器学习模型的整体损失来包括训练第一机器学习模型。

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