公开(公告)号：US20230051565A1

公开(公告)日：2023-02-16

申请号：US17398436

申请日：2021-08-10

Applicant: Waymo LLC

Inventor： Dillon Cower ,  Timothy Yang ,  Kunlong Gu ,  Marshall Friend Tappen

IPC: G06K9/62 ,  G06N3/04 ,  G06K9/00

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.