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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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) 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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computer vision and machine learning methods to interpret the photovoltaic (PV) solar farm's condition and perform various inspections and anomaly detection. The research will draw from state-of-art
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”. Research topics on vision based techniques for vibration measurements, artificial intelligence techniques, data analysis and signal processing techniques for structural health monitoring are covered in
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-athletes. Leveraging state-of-the-art artificial intelligence (AI), markerless motion capture and stereo vision technologies, this research will tackle critical challenges in biomechanics and sports science
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Inclusion Swinburne has become a world-class university, driving social and economic impacts through science, technology, and innovation. As a dual-sector university, our vision is for people and technology
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Vision and Edge Computing'. PhD candidates involved in this project will be trained in the emerging field of smart infrastructure, which is critical for Australian society in the coming decade
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to their culture and pay our respects to their Elders past and present. View our vision towards reconciliation . The Opportunity Gain experience working with industry to solve real-world problems while you earn your
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decision-making Prototype and test digital tools in a real-world practice environment Contribute to both immediate practical improvements and longer-term strategic visions for architectural practice
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-reality application development; modern AI techniques (such as computer vision or large multimodal language models); and/or human-computer interaction. Our industry partners are developing software