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group has implemented state-of-the-art deep learning for underwater communications; deep learning models underwater environment based on real data. Our preliminary study shows that state-of-the-art deep
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to frailty assessment could be beneficial. Manual measurements from CT scans, however, are labor-intensive and subject to observer variability. The advent of deep learning in medical imaging presents a
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) before the human eye can see them. The principal aim of this PhD research program is to develop methods to improve the hyperspectral image classification using deep learning techniques. The developed
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the optimisation strategies to enhance the performance of complex machine learning models such as deep learning model and large language model. Applicants need to have strong background and track records of research
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agents. Your research will explore how reinforcement learning, multi-agent cooperation and generative worldmodels can deliver adaptive strategies that thrive amid volatile, multi-asset markets, micro
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deep learning theory, Bayesian statistics, and generative modelling, this work will advance our understanding of both the capabilities and vulnerabilities of modern AI systems. This will have potential
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requiring long-term strategies of building trust to gain access to the object of research. Fieldwork may consist of deep immersion in one place or research in a number of sites – in either case, the onus is
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deep learning. The purpose of this scholarship is to support a PhD student to contribute to the advancement of infrastructure monitoring technologies with strong industry collaboration. Student type
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interaction and human motion analysis Prior knowledge of machine learning/deep learning applied to motion analysis (e.g., relevant courses and research experience) would be an advantage IELTS score of 6.5
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structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data analysis techniques, are preferred. Application process To apply