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., Aggarwal, C. C., & Salehi, M. (2025). CARLA: Self-supervised contrastive representation learning for time series anomaly detection. Pattern Recognition, 157, 110874. [2] Zamanzadeh Darban, Z., Webb, G. I
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This project examines how films produced in Asian markets perform in terms of commercial success and critical recognition using real-world industry data. Students will compile a dataset of films
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to examine vast amounts of textual data, identifying keywords, phrases, and sentiment that may indicate extremist views or intentions. Analysing audio involves techniques such as speech recognition, keyword
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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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, course design, and teaching quality monitoring to ensure an exceptional student experience, while expanding the Higher Degree by Research (HDR) program. Partnerships & Collaboration: Cultivating
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at prediction and pattern recognition tasks but still fails at very simple planning and decision-making problems. This project will develop predictive and prescriptive analytics algorithms that combine
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Over the past decades, we have witnessed the emergence and rapid development of deep learning. DL has been successfully deployed in many real-life applications, including face recognition, automatic