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(preferrable) About Swinburne University of Technology Swinburne’s strategy draws upon our understanding of future challenges. We choose to build Swinburne as the prototype of a new and different university
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part of an innovative project that not only benefits the construction industry but also sets a precedent for using technology to bridge gender gaps in various sectors. Eligibility You will need to: meet
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fall detection would be from video as it does not require wearing a device and remembering to charge it and so on. But computer vision-based falls detection in the elderly can be problematic due
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revolutionized the field of artificial intelligence, leading to remarkable advancements across many applications ranging from image classification to natural language processing. Despite these successes
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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development lifecycle greatly improves its quality and productivity. Here calls for a systematic development lifecycle for the DL systems. Due to the fundamentally different programming paradigm and logic
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and communication skills in healthcare. You will use sensor-technology to capture multimodal ‘trace’ data including gestures, speech, workspace spatial layout and manual handling of objects. You will
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. Methods To make this pre-trained model, the student will script a virtual mouse model 13 to traverse through common behavioural apparatuses within a realistic simulation tool called Unreal Engine 14