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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
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Assessment Systems: Toward Trustworthy AI for Complex Educational Evaluation Image and Video Analysis Using Machine Learning Algorithms Mathematical and Computational Neuroscience, from neural data and network
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for Pollinator Monitoring: Train and optimise deep learning models for pollinator detection and classification using annotated image datasets. Post-processing object tracking algorithms will be incorporated
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