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Ulster University.

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Semi-Automated Data Labelling. Jun Liu - Reader in Computer Science, Director of Artificial Intelligence Research Centre Federico Cruciani - Senior Research Fellow Aftab Ali - Lecturer in Computing (Internet of Things) Muhammad Asim Ali - PhD Sai Dixit Brahmam Garu Lingineni – Associate Researcher.

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Challenges of Data labelling. Error-Prone. Time-Consuming.

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The SADL project aims at investigating methods that can support and partially automate the annotation, including: Label Propagation Self-Supervised and Semi-Supervised Methods Reinforcement Learning from Human Feedback (RLHF) Dealing with Class Imbalance and Bias Few-Shot Learning.

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Proposed Solution Integration of Unsupervised, Self-Supervised, and Few-Shot Learning AI lifecycle management Reduced Human Interaction in Feedback Loop Monitoring for Biases and Data Imbalance Explainable and trustworthy AI.

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Current moment in Phase - 1. Phase I – Requirements Gathering, State-of-theart Assessment and Architectural Design.

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Conclusions and Future Work. With Phase I almost completed and having conducted a literature review of existing technologies, the next steps will include preliminary experimentation evaluating techniques on a common benchmark. Based on the results of these experiments, the combination of identified suitable techniques will be used to design a novel architecture..