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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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aims to explore who takes physics and astrophysics major units, why they pursue them, and what obstacles they may face. There are a number of research questions under this umbrella. Computational
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Embryology (MCE) program. About the Role This position plays a vital role in maintaining the MCE program's excellence, focusing on practical components, integrating innovative teaching and assessment methods
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anomalies in evolving graphs. In this research proposal, our aim is to explore the parallels of deep learning and anomaly detection in dynamic graphs. In particular we are interested to redesign deep neural
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the area of end-to-end modular autonomous driving using computer vison and deep learning methods. This includes developing an efficient and interpretable image processing, vision-based perception and
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with Turning Point's helpline service, students on the Next Generation of Graduates in AI in Mental Health program will have the opportunity to enhance the capabilities of these helplines using data
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cooperating with each other, but in many cases competing for individual gains. This structure may not always work for the benefit of science. The purpose of this project is to use game theory and computational
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that are constructed in a way that is inspired by what we know about self-awareness circuits in the brain and the field of self-aware computing. The project will advanced state of the art AI for NLP or vision or both
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the brain, as well as the latest AI methods and examine what if any consciousness current AI methods might have and how we might define whether an AI is conscious based on what we know about consciousness in
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the local and global Japanese teaching communities. This includes seeking out opportunities to collaborate with peers and staying informed on innovative teaching methods in language education. In