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Fleshy-fruited Myrtaceae, comprising nearly half of the ~6,000 species, represent a key evolutionary innovation linked to diversification and dispersal. This project investigates the ecological and
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creating robust, low cost, and real-time edge-AI algorithms capable of accurately classifying diverse marine species and debris under complex and dynamic underwater conditions. The demand for such a low-cost
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. Analysis of images will investigate the efficacy of manual digital approaches (e.g., Dot Dot Goose) and the development of a marine litter characterisation and quantification algorithm for automated analysis
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