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Grant Award View - GA2694
Towards interpretable deep learning with limited examples
GA ID:
GA2694
Agency:
Australian Research Council
Approval Date:
10-Nov-2017
Publish Date:
20-Feb-2018
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
1-Jan-2018 to 31-Dec-2021
Original: 1-Jan-2018 to 31-Dec-2020
Value (AUD):
$392,884.00
(GST inclusive where applicable)
Variations:
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 17/18 Discovery
Grant Program:
Discovery Projects
Grant Activity:
Towards interpretable deep learning with limited examples
Purpose:
Existing visual concept detection systems are incapable of detecting ever-evolving concepts in daily life. This project aims to extract patterns that describe the semantics of visual concepts and to develop or adapt knowledge transfer learning technologies for new concepts with limited examples. The expected outcomes will provide major technological breakthroughs for building efficient and interpretable learning systems for visual analysis and will open an entirely new research direction: interpretable deep learning with communication mechanism. This new field and its technologies will help us to recognise misuse of home patient medical devices and unauthorised activity, and enable us to devise effective responses to prevent cyberattacks.
Internal Reference ID:
DP18 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
University of Technology Sydney
Recipient ABN:
77 257 686 961
Grant Recipient Location
Suburb:
ULTIMO
Town/City:
ULTIMO
Postcode:
2007
State/Territory:
NSW
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
NSW
Postcode:
2007
Country:
AUSTRALIA