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, sociological, economic and web data this project will apply machine learning to build a recommendation engine that can provide life advice and predictions to individuals based on their current life situation and
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With success stories ranging from speech recognition to self-driving cars, machine learning (ML) has been one of the most impactful areas of computer science. ML’s versatility stems from the wealth
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based on matched-filter statistics. Detecting the unknown relies on the development of complex algorithms at the forefront of statistics, machine learning, and data science. This multi-disciplinary
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Project description: Nowadays, data-driven machine learning algorithms are well suited to solve real-world problems that require high-level prediction accuracy. However, it seems as if nothing beats
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The world is dynamic and in a constant state of flux, yet most machine learning models learn static models from a dataset that represents a single snapshot in time. My group's research is
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On-device machine learning (ML) is rapidly gaining popularity on mobile devices. Mobile developers can use on-device ML to enable ML features at users’ mobile devices, such as face recognition
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Machine learning has recently made significant progress for medical imaging applications including image segmentation, enhancement, and reconstruction. Funded as an Australian Research Council
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"A picture is worth a thousands words"... or so the saying goes. How much information can we extract from an image of an insect on a flower? What species is the insect? What species is the flower? Where was the photograph taken? And at what time of the year? What time of the day? What was the...
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of statistical signal processing, inference, machine learning and dynamical systems theory to develop new semi-analtyical filtering approaches for state and parameter estimation to infer neurophysiological
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This project aims to identify novel methods for inferring actors, activities, and other elements from short message communications. Covert communications are a specialist domain for analysis in the Law Enforcement (LE) context. In this project we aim to improve law enforcement’s understanding of...