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Tesla Published Patent 'Generating Ground Truth For Machine Learning From Time Series Elements'

by Eva Fox August 06, 2020

Tesla Published Patent 'Generating Ground Truth For Machine Learning From Time Series Elements'

Deep learning systems used for applications such as autonomous driving are developed by training a machine learning model. Typically, the performance of the deep learning system is limited at least in part by the quality of the training set used to train the model.

In many instances, significant resources are invested in collecting, curating, and annotating the training data. Traditionally, much of the effort to curate a training data set is done manually by reviewing potential training data and properly labeling the features associated with the data.

The effort required to create a training set with accurate labels can be significant and is often tedious. Moreover, it is often difficult to collect and accurately label data that a machine learning model needs improvement on. Therefore, there exists a need to improve the process for generating training data with accurate labeled features.

Tesla published patent 'Generating ground truth for machine learning from time series elements'

Patent filing date: February 1, 2019
Patent Publication Date: August 6, 2020


FIG. 1 is a block diagram illustrating an embodiment of a deep learning system for autonomous driving.
Source: Tesla patent

The patent disclosed a machine learning training technique for generating highly accurate machine learning results. Using data captured by sensors on a vehicle a training data set is created. The sensor data may capture vehicle lane lines, vehicle lanes, other vehicle traffic, obstacles, traffic control signs, etc.

Odometry and other similar sensors capture vehicle operating parameters such as vehicle speed, steering, orientation, change in direction, change in location, change in elevation, change in speed, etc. The captured data sets are transmitted to a training server for creating a training data set. The training data set is used to train a machine learning model for generating highly accurate machine learning results.

Tesla strives to achieve Level 5 of autonomy, therefore it is very important to correctly develop all the processes and methods that, as a result, will help the company achieve its goal.




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