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: Addressing the Crisis of Local Visual News in Regional and Remote Australia. More information about this project can be found here: https://www.cenevox.com/?page_id=196 The PhD Scholarship is attached
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of learnt features in deep neural networks. Specifically, we aim to: • Develop methodologies to interpret and visualize the features learnt by neural networks in a human-understandable manner. • Investigate
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detection and visualization, physics modelling and vibration characteristic identification techniques will be included in the digital twin frameworks. AI techniques will be further developed for simulating
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for a strategic and challenging PhD position with the topic ‘Direct visual process quality feedback to optimal machine operation in sustainable manufacturing’, under the supervision of Prof. Jeroen De
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soil C and N cycling, non-destructive visualization of soil structure and plant roots using X-ray CT Micro2Soil Laboratory, Department of Biochemistry and Microbiology, FW-UGent (prof. Caroline De Tender