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time challenges in managing data volumes (especially given the 3D format), and impacts related to digital slide and storage formats the relationship of these issues to Quality Assurance programs in
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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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of techniques it offers, making ML seem an excellent tool for any task that involves building a model from data. Nevertheless, ML makes an implicit overarching assumption that severely limits its applicability
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their performance evaluated in terms of classification accuracy, computational speed, and overall usability. Required knowledge Deep learning (CNNs, Transformers) and computer vision Knowledge distillation for model
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traditional and advanced optimization techniques, including analytical models, simulation-based approaches, and data-driven algorithms. The research also considers practical constraints such as cost, process
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and the external research community. Working as part of a specialist platform, you will support researchers through hands-on laboratory work, coordination of technical services, data handling and
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the endless possibilities of digital sound, allowing the plucking of sounds out of thin air. URLs and Further Reading https://airsticks.xyz/ Ilsar, A.A., 2018. The AirSticks: a new instrument for live
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-reported data. While informative, self-reported data can be susceptible to bias, poor memory, and incorrect self-assessment. This project will complement this self-reported measurement of feedback literacy
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Nowadays more and more intelligence software solutions emerge in our daily life, for example the face recognition, smart voice assitants, and autonomous vehicle. As a type of data-driven solutions
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the observer. Active Goal Recognition extends Goal Recognition by also assigning the data collection task to the observer. This Ph.D. project will provide a unified probabilistic and decision-theoretic