Discovery Early Career Researcher Award - Grant ID: DE240100149
Funder
Australian Research Council
Funding Amount
$462,044.00
Summary
Adaptive and Efficient Robot Positioning Through Model and Task Fusion. This project aims to create fit-for-purpose positioning systems that continuously adapt to diverse and changing environments. The project expects to contribute to the knowledge across robotics, computer vision, and neuromorphic computing. Expected outcomes of this project include ground-breaking place recognition techniques that address two fundamental limitations in the state-of-the-art: continuous adaptation, critically im ....Adaptive and Efficient Robot Positioning Through Model and Task Fusion. This project aims to create fit-for-purpose positioning systems that continuously adapt to diverse and changing environments. The project expects to contribute to the knowledge across robotics, computer vision, and neuromorphic computing. Expected outcomes of this project include ground-breaking place recognition techniques that address two fundamental limitations in the state-of-the-art: continuous adaptation, critically important in safety-critical systems, and energy efficiency, critically important in resource-constrained systems. This should provide significant benefits, such as accelerated deployment of mobile robots, drones and augmented reality solutions in manufacturing, defence, healthcare, household, and space.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230100477
Funder
Australian Research Council
Funding Amount
$421,554.00
Summary
Advancing Human Perception: Countering Evolving Malicious Fake Visual Data. The aim of this project is to provide new effective and generalisable deepfake detection methods for automatically detecting maliciously manipulated visual data generated by misused artificial intelligence (AI) techniques. It will present innovative computer vision and image processing knowledge and techniques, enabling the developed methods to advance human perception in recognising fake data, enhance cybersecurity, and ....Advancing Human Perception: Countering Evolving Malicious Fake Visual Data. The aim of this project is to provide new effective and generalisable deepfake detection methods for automatically detecting maliciously manipulated visual data generated by misused artificial intelligence (AI) techniques. It will present innovative computer vision and image processing knowledge and techniques, enabling the developed methods to advance human perception in recognising fake data, enhance cybersecurity, and protect privacy in AI applications. The anticipated outcomes should provide significant benefits to a wide range of applications, such as providing timely alerts to the media, government organisations, and the industry about misleading fake visual data, and preventing financial crimes on synthetic identity fraud.Read moreRead less