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innovative computer-vision solutions to advance new cotton varieties. By incorporating expertise in plant phenotyping, engineering, image collection, computer vision, and deep learning, you will essentially
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implement machine learning algorithms for complex data analysis. Utilise advanced programming skills (Python, MATLAB, C) and image processing libraries to develop computational solutions. Publish research
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mechanical loading of such samples. The focus of the PhD project will be to use machine learning techniques to better understand the interplay between the crystal orientations and deformation patterns in a
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very high resolution, suitable for detecting photovoltaic modules and the cleanliness of solar panels. These images and other data can be processed by computer vision and machine learning methods
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Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months ago
approaches to model uncertainty for learned computer vision systems, including dense prediction. The position will develop novel methods for deep learning in computer vision that accurately quantify their own
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variable models (e.g., CLIP, GLIP, MaskCLIP). Knowledge of Transferability in Machine Learning is desirable. Knowledge in Active Learning is desirable. Programming skills and experience with dataset
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. The underwater acoustic communication technologies will help. The school is focusing on research in AI/machine learning and signal processing which are the research areas in this proposed project. We have
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data
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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
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technologies, social structures, and networks. Effective C2 organisational systems are critical not only to military settings, but also to the operation of many civil domains, including emergency response