Discovery Early Career Researcher Award - Grant ID: DE190101473

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/DE190101473

Funding Status
Closed

Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the .

Funded Activity Summary

Feature-dependent label noise learning for big data analytics. This project aims to equip machines with the ability to robustly harness feature-dependent label noise from big data. The project expects to produce the potential to explore and exploit the weakly supervised information to better understand, interpret, and infer big data. Expected outcomes of this project include theoretical foundations for learning with label noise in the real-world scenarios and the next generation of intelligent systems to accommodate noisily annotated big data. This project should benefit science, society, and the economy nationally and internationally through the applications in the areas of artificial intelligence, cybersecurity, and big data analytics.

Funded Activity Details

Start Date: 01-06-2019

End Date: 31-05-2022

Funding Scheme: Discovery Early Career Researcher Award

Funding Amount: $387,000.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Pattern Recognition and Data Mining | Computer Vision | Artificial Intelligence and Image Processing

ANZSRC Socio-Economic Objective (SEO)

Expanding Knowledge in the Information and Computing Sciences | Film and Video Services (excl. Animation and Computer Generated Imagery) | Information Processing Services (incl. Data Entry and Capture) |

Other Keywords

Artificial Intelligence and Image Processing | Computer Vision | Expanding Knowledge in the Information and Computing Sciences | Film and Video Services (excl. Animation and Computer Generated Imagery) | Information Processing Services (incl. Data Entry and Capture) | Pattern Recognition and Data Mining

Related Links