Nordic Machine Intelligence https://journals.uio.no/NMI <p>Nordic Machine Intelligence (NMI) is a non-commercial, open-access , peer-reviewed journal and thus qualifies to be a diamond open-access journal. The journal publishes original research articles, literature reviews, conference articles related to NORA's Norwegian and Nordic conferences, articles related to the <a href="https://www.nora.ai/Competition/">NMI Challenge</a>, statements and other educational material within all aspects of artificial intelligence.</p> en-US anne.hakansson@uit.no (Anne Håkansson) b.j.singstad@fys.uio.no (Bjørn-jostein Singstad) Fri, 03 Jun 2022 11:03:29 +0200 OJS 3.3.0.11 http://blogs.law.harvard.edu/tech/rss 60 Hierarchical Object Detection applied to Fish Species https://journals.uio.no/NMI/article/view/9452 <p>Gathering information of aquatic life is often based on timeconsuming<br />methods utilizing video feeds. It would be beneficial<br />to capture more information cost-effectively from video feeds.<br />Video based object detection has an ability to achieve this.<br />Recent research has shown promising results with the use of<br />YOLO for object detection of fish. As underwater conditions<br />can be difficult and thus fish species are hard to discriminate.<br />This study proposes a hierarchical structure-based YOLO Fish<br />algorithm in both the classification and the dataset to gain<br />valuable information. With the use of hierarchical classification<br />and other techniques. YOLO Fish is a state-of-the-art object<br />detector on Nordic fish species, with an mAP of 91.8%. The<br />algorithm has an inference time of 26.4 ms, fast enough to<br />run on real-time video on the high-end GPU Tesla V100.</p> Dr. Aditya Gupta, Espen Stausland Kalhagen, Ørjan Langøy Olsen, Dr. Morten Goodwin Copyright (c) 2022 Nordic Machine Intelligence https://creativecommons.org/licenses/by/4.0 https://journals.uio.no/NMI/article/view/9452 Fri, 03 Jun 2022 00:00:00 +0200