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tissues or reveal micro- or nano-structural features, like the small air sacs in lungs. To overcome these limitations, alternative X-ray imaging methods have been developed: X-ray phase-contrast and dark
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analysis, contextual analysis, audio feature extraction, and machine learning models to identify and assess potentially dangerous content. Similarly, computer vision models are implemented to analyse images
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technologies will affect them. It is our anticipation that the work will commence with, in parallel, the survey for collecting the data and a comparison of machine learning methods on artificial pseudo-randomly
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optimisation models (e.g. using MiniZinc) and solving methods to demonstrate the transformative potential of optimisation technology in this application. Collaboration will be key, as you’ll join the DSAI’s
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People with disabilities are excluded from the assistive technology creation process because the methods and tools that are used are inaccessible. This leads to missed opportunities to create more
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methods dealing with model complexity - e.g., AIC, BIC, MDL, MML - can enhance deep learning. References: D. L. Dowe (2008a), "Foreword re C. S. Wallace ", Computer Journal , Vol. 51, No. 5 (Sept. 2008
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The brain is a complex system and monitoring and imaging methods to observe critical neurophysiological variables underlying brain function are limited. This project works at the intersection
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, computer games) and a wide variety of solution methods have been proposed. Once a plan is computed, execution proceeds under the supervision of a human operator who is free to modify and adjust the plan
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. Expected outcomes: The student will learn inference and representation learning methods for network data. The knowledge can be easily used to analyse other networks, including but not limited to social
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time. In this project, we propose a method for identifying and classifying such emerging asynchronous trends. The goal is to be able to predict how a new emerging trend will develop using similar