Blar i Brage IMR på forfatter "Ordonez, Alba"

Viser treff 1-5 av 5

    • 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 ...

    • 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. ...

    • Evaluation of echosounder data preparation strategies for modern machine learning models 

      Ordonez, Alba; Utseth, Ingrid; Brautaset, Olav; Korneliussen, Rolf; Handegard, Nils Olav (Peer reviewed; Journal article, 2022)
      Fish stock assessment and management requires accurate estimates of fish abundance, which are typically derived from echosounder observations using acoustic target classification (ATC). Skilled operators are regularly ...

    • 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 ...

    • Fisheries acoustics and Acoustic Target Classification - Report from the COGMAR/CRIMAC workshop on machine learning methods in fisheries acoustics 

      Handegard, Nils Olav; Andersen, Lars Nonboe; Brautaset, Olav; Choi, Changkyu; Eliassen, Inge Kristian; Heggelund, Yngve; Hestnes, Arne Johan; Malde, Ketil; Osland, Håkon; Ordonez, Alba; Patel, Ruben; Pedersen, Geir; Umar, Ibrahim; Engeland, Tom Van; Vatnehol, Sindre (Rapport fra havforskningen;2021 - 25, Research report, 2021)
      This report documents a workshop organised by the COGMAR and CRIMAC projects. The objective of the workshop was twofold. The first objective was to give an overview of ongoing work using machine learning for Acoustic Target ...