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Research scholarship funded by RMIT School of Computing Technologies. The scholarship is for 3 years; there would be a fee waiver and the standard stipend. Research scholarship funded by RMIT School of Computing Technologies. The scholarship is for 3 years; there would be a fee waiver and the...
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a digital format. Computer visions techniques have been recently developed for structural health monitoring of civil structures, including vibration displacement measurements, crack detection and
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This scholarship is jointly funded by a leading computer vision company in Australia and the STEM College of RMIT University. The research includes investigation into automated product quality
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numbers of minimally-interpretable models being used, as opposed to traditional models like decision trees, or even Bayesian and statistical machine learning models. Explanations of models are also needed
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an ARC Linkage Project focused on developing an autonomous system for detecting and quantifying structural damage in infrastructures (e.g., bridges, grain silos) using computer vision, digital twins, and
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and hands-on experience with AI and computer vision. Solid programming skills in Python, especially with PyTorch. Practical experience with deep learning projects, including working with attention
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children. Mechanistic modelling of disease transmission involves the use of computer code to represent the epidemic dynamics of infectious disease spread within the community. This allows modellers
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for estimating sustainable city size by identifying key determinants (e.g., accessibility, agglomeration, emissions, equity), testing spatial boundary sensitivity, and broadening sustainability
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) use computer vision/machine learning to quantity athlete performance. Develop new computer vision/machine learning methods to enable measurement of sports performance. Research program would make use
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Processing/Control Path Planning/Trajectory Planning Multi-Target Tracking/Multi-Object Tracking, Bayesian Filtering, Radom Finite Set filters or closely related multi-target tracking approaches in radar