Browsing Department of Mathematics by Journals "ICES Journal of Marine Science"

Now showing items 1-4 of 4

    • Addressing class imbalance in deep learning for acoustic target classification 

      Pala, Ahmet; Oleynik, Anna; Utseth, Ingrid; Handegard, Nils Olav (Journal article; Peer reviewed, 2023)
      Acoustic surveys provide important data for fisheries management. During the surveys, ship-mounted echo sounders send acoustic signals into the water and measure the strength of the reflection, so-called backscatter. ...

    • Drivers of the summer-distribution of Northeast Atlantic mackerel (Scomber scombrus) in the Nordic Seas from 2011 to 2017; a Bayesian hierarchical modelling approach 

      Nikolioudakis, Nikolaos; Skaug, Hans J.; Olafsdottir, Anna H.; Jansen, Teunis; Jacobsen, Jan Arge; Enberg, Katja (Peer reviewed; Journal article, 2019-03)
      Identifying factors that are statistically correlated with the geographical distribution dynamics of a species can facilitate our understanding of causal physiological and ecological relationships. Northeast Atlantic (NEA) ...

    • Good ethics or political and cultural censoring in science? 

      Torrissen, Ole; Glover, Kevin; Haug, tore; Misund, Ole Arve; Skaug, Hans J.; Kaiser, Matthias (Peer reviewed; Journal article, 2012)
      Peer-reviewed journals are the cornerstones to communicating scientific results. They play a crucial role in quality assurance through the review process, but they also create opportunities for discussions in the scientific ...

    • Machine learning in marine ecology: an overview of techniques and applications 

      Rubbens, Peter; Brodie, Stephanie; Cordier, Tristan; Desto Barcellos, Diogo; DeVos, Paul; Fernandes-Salvador, Jose A; Fincham, Jennifer; Gomes, Alessandra; Handegard, Nils Olav; Howell, Kerry L.; Jamet, Cédric; Kartveit, Kyrre Heldal; Moustahfid, Hassan; Parcerisas, Clea; Politikos, Dimitris V.; Sauzède, Raphaëlle; Sokolova, Maria; Uusitalo, Laura; Van den Bulcke, Laure; van Helmond, Aloysius; Watson, Jordan T.; Welch, Heather; Beltran-Perez, Oscar; Chaffron, Samuel; Greenberg, David S.; Kühn, Bernhard; Kiko, Rainer; Lo, Madiop; Lopes, Rubens M.; Möller, Klas Ove; Michaels, William; Pala, Ahmet; Romagnan, Jean-Baptiste; Schuchert, Pia; Seydi, Vahid; Villasante, Sebastian; Malde, Ketil; Irisson, Jean-Olivier (Journal article; Peer reviewed, 2023)
      Machine learning covers a large set of algorithms that can be trained to identify patterns in data. Thanks to the increase in the amount of data and computing power available, it has become pervasive across scientific ...