US 12,277,752 B2
Systems and methods for intelligent selection of data for building a machine learning model
Jelena Frtunikj, Bavaria (DE); and Daniel Alfonsetti, Auburn, ME (US)
Assigned to Volkswagen Group of America Investments, LLC, Reston, VA (US)
Filed by Argo AI, LLC, Pittsburgh, PA (US)
Filed on Aug. 3, 2023, as Appl. No. 18/364,569.
Application 18/364,569 is a continuation of application No. 17/101,633, filed on Nov. 23, 2020, granted, now 11,769,318.
Prior Publication US 2023/0377317 A1, Nov. 23, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06V 10/774 (2022.01); G06F 18/2115 (2023.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01); G06V 10/20 (2022.01); G06V 10/772 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06V 20/58 (2022.01); G06V 20/64 (2022.01)
CPC G06V 10/774 (2022.01) [G06F 18/2115 (2023.01); G06F 18/2148 (2023.01); G06N 20/00 (2019.01); G06V 10/255 (2022.01); G06V 10/772 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06V 20/58 (2022.01); G06V 20/588 (2022.01); G06V 20/64 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method for selecting data for building a machine learning model, the method comprising:
receiving, from a plurality of sensors, a plurality of unlabeled sensor data logs corresponding to surroundings of an autonomous vehicle;
identifying one or more trends associated with a training dataset comprising a plurality of labeled data logs, the training dataset being used for training a machine learning model;
selecting a subset of the plurality of unlabeled sensor data logs that have an importance score greater than a threshold, the importance score being assigned to each of the plurality of unlabeled sensor data logs in the subset using a function determined using the one or more trends; and
using the subset of the plurality of unlabeled sensor data logs for updating the machine learning model to generate an updated model.