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manufacturing, this automated ultrasonic system provides real-time, accurate measurements without altering the material structure. By incorporating robotic systems, advanced signal processing, and integration
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with improved accuracy, scalability, and generalisation, understanding and explaining how AI models generate specific results remains a major challenge. XAI comprises methods and processes that help
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, in the form of smart glasses, to detect chewing and swallowing eating gestures and wearable cameras to identify food types and caloric content through image processing techniques. Specifically
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) to detect 'structural biomarkers' (signatures) within the primary tumour, distant organs, nail and hair samples (collagen/keratin). NISTA then uses AI-driven processing parameters to transform raw diffraction
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Fleurentin, Georgios Exarchakis, Alexandros Karargyris, Nicolas Padoy, Dissecting self-supervised learning methods for surgical computer vision, Medical Image Analysis, Vol 88, 2023, 102844 Chengang Dong, and
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to ensure both the privacy of data and the security of the network itself. Federated learning (FL), a decentralised machine learning paradigm, presents a promising solution to these challenges. In contrast
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and efficiencies, such as automated home systems, enhanced healthcare monitoring, optimized manufacturing processes, and more [2]. Despite their advantages, IoT devices pose substantial cybersecurity
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body movement (IMU), can provide a complete picture of a person’s wellbeing. EMG sensors help understand muscle function in people with neurological conditions. GSR sensors monitor stress by measuring