Invention Grant
- Patent Title: Training a neural network to determine pedestrians
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Application No.: US16773339Application Date: 2020-01-27
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Publication No.: US11574494B2Publication Date: 2023-02-07
- Inventor: Nikita Jaipuria , Aniruddh Ravindran , Hitha Revalla , Vijay Nagasamy
- Applicant: Ford Global Technologies, LLC
- Applicant Address: US MI Dearborn
- Assignee: Ford Global Technologies, LLC
- Current Assignee: Ford Global Technologies, LLC
- Current Assignee Address: US MI Dearborn
- Agency: Bejin Bieneman PLC
- Agent Frank A. MacKenzie
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06V10/94 ; G06V40/10 ; G05D1/02 ; G06N3/04 ; G06F3/01

Abstract:
A training system for a neural network system and method of training is disclosed. The method may comprise: receiving, from a sensor, an image frame captured while an operator is controlling a vehicle; using an eye-tracking system associated with the sensor, monitoring the eyes of the operator to determine eyeball gaze data; determining, from the image frame, a plurality of pedestrians; and iteratively training the neural network system to determine, from among the plurality of pedestrians, the one or more target pedestrians using the eyeball gaze data and an answer dataset that is based on the eyeball gaze data, wherein the determined one or more target pedestrians have a relatively-higher probability of collision with the vehicle than a remainder of the plurality of pedestrians.
Public/Granted literature
- US20210232812A1 TRAINING A NEURAL NETWORK TO DETERMINE PEDESTRIANS Public/Granted day:2021-07-29
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