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-disciplinary team of clinician scientists and computer scientists to develop diagnosis/predictive/treatment/robotics surgery models of diseases of interest using multimodal medical data, consisting of images
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world, and with world-class photonic facilities at Monash. "Quantum nanophotonic chip" "Multimode imaging through ultrathin meta-optics" "Advancing optical imaging with flat optics" "Machine-learning
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for monitoring and controlling the brain with medical devices and imaging brain activity in new and important ways. Required knowledge Statistical signal processing, Statistical Inference, Machine learning, Deep
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systems. The fast growth, practical achievements and the overall success of modern approaches to AI guarantees that machine learning AI approaches will prevail as a generic computing paradigm, and will find
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techniques. It may also include hardware development of wearable assistive devices that use audio and haptic feedback. Required knowledge Image processing Computer vision Deep learning Programming (Python, C
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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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"A picture is worth a thousands words"... or so the saying goes. How much information can we extract from an image of an insect on a flower? What species is the insect? What species is the flower
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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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. The latest advanced techniques in machine learning and computer vision for image content analysis will be applied to generate data for dynamic species distribution models. This data will in turn be used
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the simple equation that more training data = better performance. Learning—in particular, the advanced deep learning methods, like BERT for NLP and ResNet for image processing—often require thousands