Timothy C Yang

US Patent:

20230051565, Feb 16, 2023

Filed:

Aug 10, 2021

Appl. No.:

17/398436

Inventors:

- Mountain View CA, US
Timothy Yang - Redwood City CA, US
Kunlong Gu - Belmont CA, US
Marshall Friend Tappen - Bainbridge Island WA, US

International Classification:

G06K 9/62
G06N 3/04
G06K 9/00

Abstract:

A method for determining hard example sensor data inputs for training a task neural network is described. The task neural network is configured to receive a sensor data input and to generate a respective output for the sensor data input to perform a machine learning task. The method includes: receiving one or more sensor data inputs depicting a same scene of an environment, wherein the one or more sensor data inputs are taken during a predetermined time period; generating a plurality of predictions about a characteristic of an object of the scene; determining a level of inconsistency between the plurality of predictions; determining that the level of inconsistency exceeds a threshold level; and in response to the determining that the level of inconsistency exceeds a threshold level, determining that the one or more sensor data inputs comprise a hard example sensor data input.