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While deep learning has shown remarkable performance in medical imaging benchmarks, translating these results to real-world clinical deployment remains challenging. Models trained on data from one
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The project involves building and curating a comprehensive food image dataset suitable for mobile AI applications. High-accuracy deep learning models will be trained on this dataset and then
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Deepfakes, derived from "deep learning" and "fake," involve techniques that merge the face images of a target person with a video of a different source person. This process creates videos where
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. This would provide thousands of diverse example images with corresponding body part locations. These data would be used to train a deep learning model 5, 7 . The model’s high-quality body part predictions may
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Australia. The scholarship was created in honour of Ric (Frederic) Bouvier who was an icon in the evolution of ambulance services and the paramedic profession in Australia. Total scholarship value $10,000
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This project aims to employ advanced machine learning techniques to analyse text, audio, images, and videos for signs of harmful behaviour. Natural language processing algorithms are utilized
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“Revealing Order in Organic Semiconductors with Cryo-Electron Microscopy.” The successful candidate will apply and develop advanced cryo-electron diffraction and imaging methods to uncover structure–property
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This project aims to develop robust algorithms capable of identifying and analyzing fingertips extracted from both static images and video footage. Machine learning techniques, particularly computer
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brain state, maintain barrier integrity, and contribute to neurological disease, including brain cancer and stroke. The lab integrates advanced imaging, omics approaches, mouse genetics and flow cytometry
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research in areas such as machine learning, clinical decision-support, medical imaging, and data-driven health services innovation. The position is expected to develop an independent research profile