Invention Grant
- Patent Title: Image annotation for deep neural networks
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Application No.: US17337789Application Date: 2021-06-03
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Publication No.: US11975738B2Publication Date: 2024-05-07
- Inventor: Gurjeet Singh , Apurbaa Mallik , Rohun Atluri , Vijay Nagasamy , Praveen Narayanan
- 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: B60W60/00
- IPC: B60W60/00 ; G06T3/4053 ; G06T7/11 ; G06T11/20 ; G06V20/58

Abstract:
A first image can be acquired from a first sensor included in a vehicle and input to a deep neural network to determine a first bounding box for a first object. A second image can be acquired from the first sensor. Input latitudinal and longitudinal motion data from second sensors included in the vehicle corresponding to the time between inputting the first image and inputting the second image. A second bounding box can be determined by translating the first bounding box based on the latitudinal and longitudinal motion data. The second image can be cropped based on the second bounding box. The cropped second image can be input to the deep neural network to detect a second object. The first image, the first bounding box, the second image, and the second bounding box can be output.
Public/Granted literature
- US20220388535A1 IMAGE ANNOTATION FOR DEEP NEURAL NETWORKS Public/Granted day:2022-12-08
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