Skip to main content

Honours and Minor Thesis projects

Displaying 151 - 160 of 224 honours projects.


Primary supervisor: Wray Buntine

Multi-label classification (MLC), which simultaneously assigns several labels to each instance, is critical in a wide variety of domains. One of the most difficult is a subset of data categorisation in which classes are arranged hierarchically and objects can be allocated to many paths of the class hierarchy concurrently. This is referred to as hierarchical multi-label classification (HMC), and it is useful for text classification. For example, the output of a news article may cover a variety of topics, including news, finance, and sports.

Primary supervisor: Daniel Harabor

Pathfinding is fundamental operation in video game AI: virtual characters need to move from location A to location B in order to explore their environment, gather resources or otherwise coordinate themselves in the course of play. Though simple in principle such problems are surprisingly challenging for game developers: paths should be short and appear realistic but they must be computed very quickly, usually with limited CPU resources and using only small amounts of memory.

Primary supervisor: David Taniar
Hand Hygiene

This project is part of a larger project on Hand Hygiene, which aims to address hand hygiene in hospitals by combining a suite of digital monitoring products with advanced data analytics. We expect to create a system that monitors the full user journey and performs constant data analysis through a cloud-based system.

Primary supervisor: David Taniar
Mobile Apps for Hand Hygiene Monitoring

This project is part of a larger project on Hand Hygiene, which aims to address hand hygiene in hospitals by combining a suite of digital monitoring products with advanced data analytics. We expect to create a system that monitors the full user journey and performs constant data analysis through a cloud-based system.

Primary supervisor: Chunyang Chen

Although we normally use our fingers to manipulate apps in the smart phone, that operation may not apply in some special situation e.g., checking information when holding your kids, driving, people with disability, etc. In those special scenarios, controlling the app with voice will make it much more convenient. In this study, we are trying to develop a tool to automatically map your voice to operations in mobile apps. You will work with one of my PhD students and me to deliver this exciting work which can be both published in academic and applied into the practice.

Primary supervisor: Lan Du

As a pregnancy approaches term (the point at which the foetus is considered fully developed), decisions are made about the timing of birth and the way babies are born. These decisions are incredibly challenging for clinicians and pregnant women. Digital health records, advances in big data, machine learning and artificial intelligence methodologies, and novel data visualisation capabilities have opened up opportunities for a dynamic, ‘Learning Health System’ – where data can be harnessed to inform real-time and personalised decision-making.

Primary supervisor: Lan Du

Traumatic brain injury (TBI) is an injury to the brain caused by an external force from incidents such as motor vehicle crashes, falls, assault or sports collisions. Almost seventy million individuals globally are estimated to suffer from TBI per annum [1], deeming it a major public health concern which is estimated to cost the global economy approximately $US400 billion annually [2]. Early identification of severe TBI with proper assessment and treatment lowers the risk of secondary injury and subsequent long-term disability and subsequent costs.…

Primary supervisor: Hamid Rezatofighi

Pose Tracking is the task of estimating multi-person human poses in videos and assigning unique instance IDs for each keypoint across frames. Accurate estimation of human keypoint-trajectories is useful for human action recognition, human interaction understanding, motion capture and animation.

Primary supervisor: Viviane Hessami

Information behaviour research is usually premised on access remaining available, that is on continuous access to information. Little research has been done on the ways people preserve information that they may need later on. However, with information more and more often provided online, continuous access to information cannot be guaranteed for disadvantaged groups who cannot afford the cost of digital technologies.

Primary supervisor: Jianfei Cai

Deep learning has achieved ground-breaking performance in many vision tasks in the recent years. The objective of this project is to apply the state-of-the-art deep learning based image classification/detection networks such as ResNet or Faster RCNN for classifying CT or X-Ray images.