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Grant Award View - GA68744-V1
Data synthesis to quantitatively understand and improve vision systems
GA ID:
GA68744-V1
Agency:
Australian Research Council
Approval Date:
19-Dec-2019
Variation Publish Date:
2-Aug-2021
Variation Date:
27-Jul-2021
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
1-Jan-2020 to 31-Dec-2022
Value (AUD):
$441,097.80
(GST inclusive where applicable)
Varies:
GA68744
- Data synthesis to quantitatively understand and improve vision systems
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 19/20 Discovery
Grant Program:
Discovery Early Career Researcher Award
Grant Activity:
Data synthesis to quantitatively understand and improve vision systems
Purpose:
This project aims to build high-fidelity synthetic data, to understand how a machine vision system reacts to environmental factors and consequently improve the ability of the system to generalise in the real world. This project expects to generate new knowledge in the area of computer vision using innovative techniques of data synthesis, analysis, and domain adaptation. The expected outcomes include new scientific discoveries and domain adaptation algorithms derived from synthetic data for real-world applications. The benefits are expected to be widespread across sectors such as transportation, security, and manufacturing, including safer robotic navigation, defect detection, and smart video surveillance to improve community safety.
GO ID:
GO Title:
Discovery Early Career Researcher Award for funding commencing in 2020
Internal Reference ID:
DE20 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
The Australian National University
Recipient ABN:
52 234 063 906
Grant Recipient Location
Suburb:
ACTON
Town/City:
ACTON
Postcode:
2601
State/Territory:
ACT
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
ACT
Postcode:
2601
Country:
AUSTRALIA