SINTEF search

Understanding appetitive fish behaviour patterns represents a critical challenge for developing intelligent aquaculture monitoring and feeding systems. We present a novel robust analytical framework that combines non-invasive monitoring techniques from 3D multibeam sonar data and environmental...

...https://konferanser.aqkva.no/ai-aqkva-conference/speakers...

...https://www.linkedin.com/posts/havbruksdagen_en-annen-foredragsholder-vi-er-begeistret-activity-7302700717507579904-jJMs?utm_medium=ios_app&rcm=ACoAAAGXAm0Bj9icreLG-HeCaHnTSwPYZUfVZs0&utm_source=social_share_send&utm_campaign=copy_link...

As aquaculture systems become increasingly complex, simulation tools must evolve to support intuitive, reliable, and domain-specific exploration. In our earlier work, we developed a web-based platform that combined Functional Mock-up Units (FMUs), surrogate modeling techniques, and a basic chatbot...