• Automatic interpretation of otoliths using deep learning 

      Moen, Endre; Handegard, Nils Olav; Allken, Vaneeda; Albert, Ole Thomas; Harbitz, Alf; Malde, Ketil (Peer reviewed; Journal article, 2018-12-17)
      The age structure of a fish population has important implications for recruitment processes and population fluctuations, and is a key input to fisheries-assessment models. The current method of determining age structure ...
    • Automatic interpretation of salmon scales using deep learning 

      Vabø, Rune; Moen, Endre; Smolinski, Szymon; Husebø, Åse; Handegard, Nils Olav; Malde, Ketil (Journal article; Peer reviewed, 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 ...
    • A deep learning-based method to identify and count pelagic and mesopelagic fishes from trawl camera images 

      Allken, Vaneeda; Rosen, Shale Pettit; Handegard, Nils Olav; Malde, Ketil (Journal article; Peer reviewed, 2021)
      Fish counts and species information can be obtained from images taken within trawls, which enables trawl surveys to operate without extracting fish from their habitat, yields distribution data at fine scale for better ...