• Automatic interpretation of salmon scales using deep learning 

      Vabø, Rune; Moen, Endre; Smolinski, Szymon; Husebø, Åse; Handegard, Nils Olav; Malde, Ketil (Peer reviewed; Journal article, 2021)
      For several fish species, age and other important biological information is manually inferred from visual scrutinization of scales, and reliable automatic methods are not widely available. Here, we apply Convolutional ...
    • 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. ...
    • PELFOSS (PELagic Fish Observation System Simulator) 

      Skogen, Morten D.; Handegard, Nils Olav; Holmin, Arne Johannes; Hjøllo, Solfrid Sætre; Mousing, Erik Askov; Utne, Kjell Rong; Vabø, Rune (Rapport fra havforskningen;30-2018, Research report, 2018)
      PELFOSS har utviklet en observasjonssystem-simulator for pelagisk fisk i Norskehavet. Simulatoren er en dataløype der romlig fordeling av fiskebestander fra en økosystemmodell er benyttet til å simulere ulike tokt. Disse ...