Sort by
Refine Your Search
-
Category
-
Program
-
Field
- Computer Science
- Education
- Arts and Literature
- Social Sciences
- Medical Sciences
- Psychology
- Biology
- Mathematics
- Design
- Business
- Law
- Engineering
- Statistics
- Humanities
- Electrical Engineering
- Environment
- Economics
- Physics
- Chemistry
- Linguistics
- Sports and Recreation
- Materials Science
- Earth Sciences
- 13 more »
- « less
-
Primary supervisor Pari Delir Haghighi Research area Embodied Visualisation Current federated learning architectures in mobile healthcare are limited to a centralised model without considering the
-
large number of mobile apps have been recently introduced to assist individuals with self-management of diabetes. However, these studies often provide dietary advice based on the average responses of
-
Primary supervisor Pari Delir Haghighi Research area Embodied Visualisation Mobile and continuous health monitoring has seen major advancements in recent years. The capabilities of current mobile
-
sizes or that need different control sizes due to application being internationalised into foreign languages. For this reason, Apple introduced constraint-based GUI layout under the name Auto Layout for
-
sizes or that need different control sizes due to application being internationalised into foreign languages. For this reason, Apple introduced constraint-based GUI layout under the name Auto Layout for
-
and the Australian Federal Police, and researches the ethical application of AI theories and techniques to problems of interest to law enforcement agencies. The work of the lab is applied in nature
-
and the Australian Federal Police, and researches the ethical application of AI theories and techniques to problems of interest to law enforcement agencies. The work of the lab is applied in nature
-
Research area Cybersecurity On-device machine learning (ML) is rapidly gaining popularity on mobile devices. Mobile developers can use on-device ML to enable ML features at users’ mobile devices
-
Research area Cybersecurity On-device machine learning (ML) is rapidly gaining popularity on mobile devices. Mobile developers can use on-device ML to enable ML features at users’ mobile devices
-
$432,500 – nearly 45 times the value estimated before auction. It turned out that the group behind the work had largely relied on code written by a young open source developer, who did not receive any