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Grant Award View - GA59730-V3
Adapting Deep Learning for Real-world Medical Image Datasets
GA ID:
GA59730-V3
Agency:
Australian Research Council
Approval Date:
17-Oct-2019
Variation Publish Date:
20-Oct-2021
Variation Date:
12-Oct-2021
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
1-Mar-2020 to 28-Feb-2024
Value (AUD):
$988,200.00
(GST inclusive where applicable)
Varies:
GA59730
- Adapting Deep Learning for Real-world Medical Image Datasets
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 19/20 Discovery
Grant Program:
ARC Future Fellowships
Grant Activity:
Adapting Deep Learning for Real-world Medical Image Datasets
Purpose:
The project aims to investigate new deep learning modelling approaches to leverage real-world large-scale image data sets that contain noisy and incomplete labels and imbalanced class prevalence – to enable the use of these data sets for modelling deep learning classifiers. Expected outcomes include an innovative method for modelling deep learning classifiers. The research will involve new inter-disciplinary and international collaborations with machine learning and medical image analysis research institutions. This should provide significant benefits, such as better understanding of deep learning theory, new deep learning applications that can use previously unexplored data sets, and training for the future Australian workforce.
GO ID:
GO Title:
Future Fellowships for funding commencing in 2019
Internal Reference ID:
FT19 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
The University of Adelaide
Recipient ABN:
61 249 878 937
Grant Recipient Location
Suburb:
ADELAIDE
Town/City:
ADELAIDE
Postcode:
5000
State/Territory:
SA
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
SA
Postcode:
5000
Country:
AUSTRALIA