Browsing Brage IMR by Author "Malde, Ketil"

Now showing items 1-20 of 30

    • A contrastive learning approach for individual re-identification in a wild fish population 

      Olsen, Ørjan Langøy; Sørdalen, Tonje Knutsen; Goodwin, Morten; Malde, Ketil; Knausgård, Kristian Muri; Halvorsen, Kim Aleksander Tallaksen (Peer reviewed; Journal article, 2023)
      In both terrestrial and marine ecology, physical tagging is a frequently used method to study population dynamics and behavior. However, such tagging techniques are increasingly being replaced by individual re-identification ...

    • 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 ...

    • Annotating otoliths with a deep generative model 

      Bojesen, Troels Arnfred; Denechaud, Côme; Malde, Ketil (Peer reviewed; Journal article, 2023)
      Otoliths are a central information source for fish ecology and stock management, conveying important data about age and other life history for individual fish. Traditionally, interpretation of otoliths has required skilled ...

    • Automatic interpretation of otoliths using deep learning 

      Moen, Endre; Handegard, Nils Olav; Allken, Vaneeda; Albert, Ole Thomas; Harbitz, Alf; Malde, Ketil (Journal article; Peer reviewed, 2018)
      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 (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 ...

    • Characterization of a novel RXR receptor in the salmon louse (Lepeophtheirus salmonis, Copepoda) regulating growth and female reproduction 

      Eichner, Christiane; Dalvin, Sussie Trine; Skern-Mauritzen, Rasmus; Malde, Ketil; Kongshaug, Heidi; Nilsen, Frank (Journal article; Peer reviewed, 2015-02-14)
      Nuclear receptors have crucial roles in all metazoan animals as regulators of gene transcription. A wide range of studies have elucidated molecular and biological significance of nuclear receptors but there are still a ...

    • 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 (Peer reviewed; Journal article, 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 ...

    • 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. ...

    • EST resources and establishment and validation of a 16 k cDNA microarray from Atlantic cod (Gadus morhua) 

      Edvardsen, Rolf B.; Malde, Ketil; Mittelholzer, Christian; Taranger, Geir Lasse; Nilsen, Frank (Journal article; Peer reviewed, 2010-06-28)
      The Atlantic cod, Gadus morhua, is an important species both for traditional fishery and increasingly also in fish farming. The Atlantic cod is also under potential threat from various environmental changes such as pollution ...

    • EST resources and establishment and validation of a 16 k cDNA microarray from Atlantic cod (Gadus morhua) 

      Edvardsen, Rolf B.; Malde, Ketil; Mittelholzer, Christian; Taranger, Geir Lasse; Nilsen, Frank (Journal article; Peer reviewed, 2010-06-28)
      The Atlantic cod, Gadus morhua, is an important species both for traditional fishery and increasingly also in fish farming. The Atlantic cod is also under potential threat from various environmental changes such as pollution ...

    • 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 ...

    • Genome sequencing Part 1. Final report, April 2013 

      Skern-Mauritzen, Rasmus; Malde, Ketil; Furmanek, Tomasz; Nilsen, Frank (Rapport fra Havforskningen;Nr. 11-2013, Working paper, 2013)

    • Genome wide analysis reveals genetic divergence between Goldsinny wrasse populations 

      Jansson, Eeva; Besnier, Francois; Malde, Ketil; André, Carl; Dahle, Geir; Glover, Kevin (Peer reviewed; Journal article, 2020)
      Marine fish populations are often characterized by high levels of gene flow and correspondingly low genetic divergence. This presents a challenge to define management units. Goldsinny wrasse (Ctenolabrus rupestris) is a ...

    • Human-induced evolution caught in action: SNP-array reveals rapid amphi-atlantic spread of pesticide resistance in the salmon ecotoparasite Lepeophtheirus salmonis 

      Besnier, Francois; Kent, Matthew; Skern-Mauritzen, Rasmus; Lien, Sigbjørn; Malde, Ketil; Edvardsen, Rolf B.; Taylor, Simon; Ljungfeldt, Lina; Nilsen, Frank; Glover, Kevin A. (Journal article; Peer reviewed, 2014-10-26)
      Background The salmon louse, Lepeophtheirus salmonis, is an ectoparasite of salmonids that causes huge economic losses in salmon farming, and has also been causatively linked with declines of wild salmonid populations. ...

    • Increasing Sequence Search Sensitivity with Transitive Alignments 

      Malde, Ketil; Furmanek, Tomasz (Journal article; Peer reviewed, 2013-02-14)
      Sequence alignment is an important bioinformatics tool for identifying homology, but searching against the full set of available sequences is likely to result in many hits to poorly annotated sequences providing very little ...

    • Judging a salmon by its spots: Environmental variation is the primary determinant of spot patterns in Salmo salar 

      Jørgensen, Katarina Mariann; Solberg, Monica Favnebøe; Besnier, Francois; Thorsen, Anders; Fjelldal, Per Gunnar; Skaala, Øystein; Malde, Ketil; Glover, Kevin (Journal article; Peer reviewed, 2018)
      In fish, morphological colour changes occur from variations in pigment concentrations and in the morphology, density, and distribution of chromatophores in the skin. However, the underlying mechanisms remain unresolved in ...

    • Machine intelligence and the data-driven future of marine science 

      Malde, Ketil; Handegard, Nils Olav; Eikvil, Line; Salberg, Arnt Børre (Peer reviewed; Journal article, 2019)
      Oceans constitute over 70% of the earth’s surface, and the marine environment and ecosystems are central to many global challenges. Not only are the oceans an important source of food and other resources, but they also ...

    • Machine Learning + Marine Science: Critical Role of Partnerships in Norway 

      Handegard, Nils Olav; Eikvil, Line; Jenssen, Robert; Kampffmeyer, Michael; Salberg, Arnt Børre; Malde, Ketil (Others, 2021)
      In this essay, we review some recent advances in developing machine learning (ML) methods for marine science applications in Norway. We focus mostly on deep learning (DL) methods and review the challenges we have faced in ...

    • Machine learning in marine ecology: an overview of techniques and applications 

      Rubbens, Peter; Brodie, Stephanie; Cordier, Tristan; Desto Barcellos, Diogo; DeVos, Paul; Fernandes-Salvador, Jose A; Fincham, Jennifer; Gomes, Alessandra; Handegard, Nils Olav; Howell, Kerry L.; Jamet, Cédric; Kartveit, Kyrre Heldal; Moustahfid, Hassan; Parcerisas, Clea; Politikos, Dimitris V.; Sauzède, Raphaëlle; Sokolova, Maria; Uusitalo, Laura; Van den Bulcke, Laure; van Helmond, Aloysius; Watson, Jordan T.; Welch, Heather; Beltran-Perez, Oscar; Chaffron, Samuel; Greenberg, David S.; Kühn, Bernhard; Kiko, Rainer; Lo, Madiop; Lopes, Rubens M.; Möller, Klas Ove; Michaels, William; Pala, Ahmet; Romagnan, Jean-Baptiste; Schuchert, Pia; Seydi, Vahid; Villasante, Sebastian; Malde, Ketil; Irisson, Jean-Olivier (Peer reviewed; Journal article, 2023)
      Machine learning covers a large set of algorithms that can be trained to identify patterns in data. Thanks to the increase in the amount of data and computing power available, it has become pervasive across scientific ...

    • Maternal 3’UTRs: from egg to onset of zygotic transcription in Atlantic cod 

      Kleppe, Lene; Edvardsen, Rolf B.; Kuhl, Heiner; Malde, Ketil; Furmanek, Tomasz; Drivenes, Øyvind; Reinhardt, Richard; Taranger, Geir Lasse; Wargelius, Anna (Journal article; Peer reviewed, 2012-09-01)
      Background Zygotic transcription in fish embryos initiates around the time of gastrulation, and all prior development is initiated and controlled by maternally derived messenger RNAs. Atlantic cod egg and embryo viability ...