{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:38:24Z","timestamp":1761176304985,"version":"build-2065373602"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>The crucial need for reliable, robust and un-biased biodiversity data in support of initiatives such as the 30x30 initiative, which aims to conserve 30% of the world\u2019s oceans by 2030, presents significant scientific and technological challenges. There have been advances made to automate fish biodiversity assessments using computer vision. However, the stark difference in research fields between ecology and artificial intelligence hinders the efficient use of computer vision tools for ecological tasks. This demo presents CleverFish, a novel tool designed to bridge the gap between artificial intelligence and marine biology. CleverFish tackles three core challenges of an efficient management tool: i) providing an easy-to-use graphical user interface to an AI pipeline, ii) accommodating global and video-specific in-app biodiversity assessment and iii) allowing fast and efficient extraction of temporal and spatial fish species distribution in a format understandable for ecologists. An accessible web application enables seamless integration into marine monitoring pipelines and conservation efforts.<\/jats:p>","DOI":"10.3233\/faia251431","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T10:02:30Z","timestamp":1761127350000},"source":"Crossref","is-referenced-by-count":0,"title":["CleverFish: An AI-Driven Platform to Monitor and Explore Marine Ecological Resources"],"prefix":"10.3233","author":[{"given":"Kilian","family":"B\u00fcrgi","sequence":"first","affiliation":[{"name":"Universit\u00e9 C\u00f4te d\u2019Azur, CNRS, ECOSEAS, France"},{"name":"Universit\u00e9 C\u00f4te d\u2019Azur, Inria, CNRS, I3S, Team Maasai, France"}]},{"given":"Stephane","family":"Petiot","sequence":"additional","affiliation":[{"name":"Universit\u00e9 C\u00f4te d\u2019Azur, Institut 3IA C\u00f4te d\u2019Azur, Techpool, France"}]},{"given":"C\u00e9cile","family":"Sabourault","sequence":"additional","affiliation":[{"name":"Universit\u00e9 C\u00f4te d\u2019Azur, CNRS, ECOSEAS, France"}]},{"given":"R\u00e9my","family":"Sun","sequence":"additional","affiliation":[{"name":"Universit\u00e9 C\u00f4te d\u2019Azur, Inria, CNRS, I3S, Team Maasai, France"}]},{"given":"Diane","family":"Lingrand","sequence":"additional","affiliation":[{"name":"Universit\u00e9 C\u00f4te d\u2019Azur, Inria, CNRS, I3S, Team Maasai, France"}]},{"given":"Benoit","family":"Derijard","sequence":"additional","affiliation":[{"name":"Universit\u00e9 C\u00f4te d\u2019Azur, CNRS, ECOSEAS, France"}]},{"given":"Charles","family":"Bouveyron","sequence":"additional","affiliation":[{"name":"Universit\u00e9 C\u00f4te d\u2019Azur, Inria, CNRS, Laboratoire J.A.Dieudonn\u00e9, Team Maasai, France"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251431","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T10:02:30Z","timestamp":1761127350000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251431"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251431","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}