Blar i Publikasjoner fra CRIStin på forfatter "Salberg, Arnt-Børre"

Viser treff 1-6 av 6

    • Acoustic classification in multifrequency echosounder data using deep convolutional neural networks 

      Brautaset, Olav; Waldeland, Anders Ueland; Johnsen, Espen; Malde, Ketil; Eikvil, Line; Salberg, Arnt-Børre; Handegard, Nils Olav (Peer reviewed; Journal article, 2020)
      Acoustic target classification is the process of assigning observed acoustic backscattering intensity to an acoustic category. A deep learning strategy for acoustic target classification using a convolutional network is ...

    • Automatic Fish Age Determination across Different Otolith Image Labs Using Domain Adaptation 

      Ordonez, Alba; Eikvil, Line; Salberg, Arnt-Børre; Harbitz, Alf; Elvarsson, Bjarki Thor (Peer reviewed; Journal article, 2022)
      The age determination of fish is fundamental to marine resource management. This task is commonly done by analysis of otoliths performed manually by human experts. Otolith images from Greenland halibut acquired by the ...

    • Deep Semi-Supervised Semantic Segmentation in Multi-Frequency Echosounder Data 

      Choi, Changkyu; Kampffmeyer, Michael; Jenssen, Robert; Handegard, Nils Olav; Salberg, Arnt-Børre (Peer reviewed; Journal article, 2023)
      Multi-frequency echosounder data can provide a broad understanding of the underwater environment in a non-invasive manner. The analysis of echosounder data is, hence, a topic of great importance for the marine ecosystem. ...

    • Deep Semi-Supervised Semantic Segmentation in Multi-Frequency Echosounder Data 

      Choi, Changkyu; Kampffmeyer, Michael; Jenssen, Robert; Handegard, Nils Olav; Salberg, Arnt-Børre (Peer reviewed; Journal article, 2023)
      Multi-frequency echosounder data can provide a broad understanding of the underwater environment in a non-invasive manner. The analysis of echosounder data is, hence, a topic of great importance for the marine ecosystem. ...

    • DeepOtolith v1.0: An Open-Source AI Platform for Automating Fish Age Reading from Otolith or Scale Images 

      Politikos, Dimitris V.; Sykiniotis, Nikolaos; Petasis, Georgios; Dedousis, Pavlos; Ordonez, Alba; Vabø, Rune; Anastasopoulou, Aikaterini; Moen, Endre; Mytilineou, Chryssi; Salberg, Arnt-Børre; Chatzispyrou, Archontia; Malde, Ketil (Peer reviewed; Journal article, 2022)
      Every year, marine scientists around the world read thousands of otolith or scale images to determine the age structure of commercial fish stocks. This knowledge is important for fisheries and conservation management. ...

    • Explaining decisions of deep neural networks used for fish age prediction 

      Ordonez, Alba; Eikvil, Line; Salberg, Arnt-Børre; Harbitz, Alf; Murray, Sean Meling; Kampffmeyer, Michael (Peer reviewed; Journal article, 2020)
      Age-reading of fish otoliths (ear stones) is important for the sustainable management of fish resources. However, the procedure is challenging and requires experienced readers to carefully examine annual growth zones. In ...