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FinFinder: Fish Identification with AI - Machine Learning/Using AI to identify marine life

City
Initially for the sea surrounding Malta, with the future aim for it to be used for the entire Mediterranean basin
Country
Malta
Stage of project
Stage 2: R&D
Sea basin regions
Mediterranean Sea
Topics
Other
Topics - other
Artificial intelligence and marine life
Categories
Business and innovation (creation, process, strategy, product, service, etc.) related to sustainable use of marine resources
Community engagement - work with local communities to solve local marine and social challenges and with high social acceptance potential
Ocean conservation
Research related to solve marine and societal challenges
Description

The project aims to leverage artificial intelligence and image processing to create an innovative algorithm for fish species identification. Prioritizing between invasive and native species, it utilizes machine learning on aquatic datasets for precise on-the-spot recognition. Key objectives include aiding in raising awareness around stakeholders and the public, marine biology research and conservation efforts. Focused initially on 3-4 species around the Maltese islands, it employs deep learning techniques and neural networks for accurate identification. The project also fosters citizen science involvement, with plans for a user-friendly database and mobile application. Beneficiaries include the public, researchers, conservationists, citizen scientists, and fishermen. Activities involve dataset training, algorithm development, interface design, and database creation. Starting with species selection and dataset preparation, it progresses through model training and application development. Contributors include AI experts, marine biologists, and citizen scientists. The project spans from inception to application deployment, aiming to enhance marine biodiversity research and conservation.