Invention Grant
- Patent Title: Automatic generation of ground truth data for training or retraining machine learning models
-
Application No.: US16521328Application Date: 2019-07-24
-
Publication No.: US11250296B2Publication Date: 2022-02-15
- Inventor: Eric Todd Brower
- Applicant: NVIDIA Corporation
- Applicant Address: US CA San Jose
- Assignee: NVIDIA Corporation
- Current Assignee: NVIDIA Corporation
- Current Assignee Address: US CA San Jose
- Agency: Shook, Hardy & Bacon L.L.P.
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06K9/62 ; G06K9/20 ; G06N3/08 ; G06Q50/26

Abstract:
In various examples, object detections of a machine learning model are leveraged to automatically generate new ground truth data for images captured at different perspectives. The machine learning model may generate a prediction of a detected object at the different perspective, and an object tracking algorithm may be used to track the object through other images in a sequence of images where the machine learning model may not have detected the object. New ground truth data may be generated as a result of the object tracking algorithms outputs, and the new ground truth data may be used to retrain or update the machine learning model, train a different machine learning model, or increase the robustness of a ground truth data set that may be used for training machine learning models from various perspectives.
Public/Granted literature
- US20210027103A1 AUTOMATIC GENERATION OF GROUND TRUTH DATA FOR TRAINING OR RETRAINING MACHINE LEARNING MODELS Public/Granted day:2021-01-28
Information query