QUT offers a diverse range of student topics for Honours, Masters and PhD study. Search to find a topic that interests you or propose your own research topic to a prospective QUT supervisor. You may also ask a prospective supervisor to help you identify or refine a research topic.

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Found 16 matching student topics

Displaying 13–16 of 16 results

Understanding responsible deployment of computer vision for urban planning

Advances in artificial intelligence (AI) offer urban planning practice many novel prospects. By the responsive use of AI, planners can effectively analyse data, improve processes, increase efficiency, and prioritise human-centric aspects of planning to develop sustainable cities. Computer vision is one of the key areas where responsible AI is applied in urban planning to revolutionise the analysis and interpretation of visual data, like images and videos captured in cities to aid decision and plan making processes. While the potential impacts …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Architecture and Built Environment

Machine learning for understanding and predicting behaviour

Understanding behaviour and predicting events is a core machine learning task, and has many applications in areas including computer vision (to detect or prediction actions in video) and signal processing (to detect events in medical signals).While a large body of research exists exploring these tasks, a number of common challenges persist including:capturing variations in how behaviours or events appear across different subjects, such that predictions can be accurately made for previously unseen subjectsmodelling and incorporating long-term relationships, such as previously …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

Analysis of professional squash matches

This project concerns computer vision and statistical analysis of performance in professional level matches in the game of squash.The goal is to use computer vision and existing systems to capture and analyse patterns of play, allowing coaches and professional players to develop strategies to improve performance, to counter particular types of play and even to tailor game plans to attack individual opponents.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

New technology and the law

Computer vision has developed to a point where machines using artificial intelligence are better and faster than humans at performing many vision-related tasks. For example, we are now often processed through customs based solely on face recognition software. Add to this the fact that the average Australian is photographed on CCTV cameras around 75 times per day. Commercial applications of face recognition technology include Microsoft's Face Application Programming Interface that can be used to classify face images based on gender, …

Study level
PhD, Master of Philosophy
School
null
Research centre(s)
null
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