Blar i Scientific Publications in Engineering Sciences på forfatter "Knausgård, Kristian Muri"

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    • Accurate Wound and Lice Detection in Atlantic Salmon Fish Using a Convolutional Neural Network 

      Gupta, Aditya; Bringsdal, Even; Knausgård, Kristian Muri; Goodwin, Morten (Peer reviewed; Journal article, 2022)
      The population living in the coastal region relies heavily on fish as a food source due to their vast availability and low cost. This need has given rise to fish farming. Fish farmers and the fishing industry face serious ...

    • Branch-Manoeuvring Capable Pipe Cleaning Robot for Aquaponic Systems 

      Knausgård, Kristian Muri; Gangenes Skar, Siv-Lene; Sanfilippo, Filippo; Buldenko, Albert; Lindheim, Henning; Lunde, Jakob; Sukarevicius, Eligijus; Robbersmyr, Kjell Gunnar (Communications in Computer and Information Science;1616, Chapter; Peer reviewed, 2022)
      Aquaponic systems are engineered ecosystems combining aquaculture and plant production. Nutrient rich water is continuously circulating through the system from aquaculture tanks. A biofilter with nitrifying bacteria breaks ...

    • Development of a Simulator for Prototyping Reinforcement Learning based Autonomous Cars 

      Holen, Martin; Knausgård, Kristian Muri; Goodwin, Morten (Peer reviewed; Journal article, 2022)
      Autonomous driving is a research field that has received attention in recent years, with increasing applications of reinforcement learning (RL) algorithms. It is impractical to train an autonomous vehicle thoroughly in the ...

    • Unlocking the potential of deep learning for marine ecology: overview, applications, and outlook 

      Goodwin, Morten; Halvorsen, Kim Aleksander Tallaksen; Jiao, Lei; Knausgård, Kristian Muri; Martin, Angela Helen; Moyano, Marta; Oomen, Rebekah Alice; Rasmussen, Jeppe Have; Sørdalen, Tonje Knutsen; Thorbjørnsen, Susanna Huneide (Peer reviewed; Journal article, 2022)
      The deep learning (DL) revolution is touching all scientific disciplines and corners of our lives as a means of harnessing the power of big data. Marine ecology is no exception. New methods provide analysis of data from ...