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Bilde av Skjelvareid, Martin
Bilde av Skjelvareid, Martin
Teacher and researcher at UiT campus Bodø Department of Computer Science and Computational Engineering martin.skjelvareid@uit.no +47 76 96 69 55 Bodø

Martin Skjelvareid

Job description

Teaching

Teaching machine learning and physics in the Bachelor's program in Computer Engineering at UiT campus Bodø. See details under the "teaching" tab.

Research

Project leader for the "MASSIMAL" project (Mapping of Algae and Seagrass using Spectral Imaging and MAchine Learning) running from 2020-2024. The project is funded by the Research Council of Norway (8 million NOK, via "young research talents") and UiT (600,000 NOK). The goal of the project is to develop a tool for accurate mapping of marine vegetation (algae/kelp/seagrass) using hyperspectral imaging from drones.

Main research interests: Mapping of marine habitats, hyperspectral imaging with drones, and machine learning/deep learning with a focus on image segmentation. Emphasis on open research with full publication of datasets and code.

Areas of Expertise:

  • Programming (Python / Matlab)
  • Hyperspectral imaging
  • Remote sensing and Geographic Information Systems (GIS)
  • Machine learning, with a focus on image processing
  • Acoustics, with a focus on ultrasound
  • Synthetic aperture imaging (mainly with ultrasound)
  • Martin Hansen Skjelvareid, Eli Rinde, Kasper Hancke, Katalin Blix, Galice Guillaume Hoarau :
    Mapping Marine Macroalgae along the Norwegian Coast Using Hyperspectral UAV Imaging and Convolutional Nets for Semantic Segmentation
    IEEE International Geoscience and Remote Sensing Symposium proceedings 2023 ARKIV / DOI
  • Martin Skjelvareid :
    Synaptus: A Matlab/Octave toolbox for synthetic aperture ultrasound imaging.
    Journal of Open Source Software (JOSS) 2022 ARKIV / DOI
  • Kathryn E. Anderssen, Svein Kristian Stormo, Torstein Skåra, Martin Hansen Skjelvareid, Karsten Heia :
    Predicting liquid loss of frozen and thawed cod from hyperspectral imaging
    Lebensmittel-Wissenschaft + Technologie 2020 ARKIV / DOI
  • Svein Kristian Stormo, Torstein Skåra, Dagbjørn Skipnes, Izumi Sone, Mats Carlehög, Karsten Heia et al.:
    In-Pack Surface Pasteurization of Capture-Based, Pre-Rigor Filleted Atlantic Cod (Gadus morhua)
    Journal of Aquatic Food Product Technology 2018 DOI
  • Martin Hansen Skjelvareid, Mette Serine Wesmajervi Breiland, Atle Mortensen :
    Ultrasound as potential inhibitor of salmon louse infestation - a small-scale study
    Aquaculture Research 2018 ARKIV / DOI
  • Martin Hansen Skjelvareid, Svein Kristian Stormo, Kristin Anna Þórarinsdóttir, Karsten Heia :
    Weakening Pin Bone Attachment in Fish Fillets Using High-Intensity Focused Ultrasound
    Foods 2017 ARKIV / DOI
  • Kathryn Elizabeth Washburn, Svein Kristian Stormo, Martin Hansen Skjelvareid, Karsten Heia :
    Non-invasive assessment of packaged cod freeze-thaw history by hyperspectral imaging
    Journal of Food Engineering 2017 ARKIV / DOI
  • Martin Hansen Skjelvareid, Karsten Heia, Stein Harris Olsen, Svein Kristian Stormo :
    Detection of blood in fish muscle by constrained spectral unmixing of hyperspectral images
    Journal of Food Engineering 2017 ARKIV / DOI
  • Martin Hansen Skjelvareid, Eli Rinde, Kasper Hancke, Katalin Blix, Galice Guillaume Hoarau :
    The MASSIMAL dataset: Hyperspectral, multispectral and RGB images of shallow coastal habitats in Norway
    2025 DATA
  • Martin Hansen Skjelvareid :
    Mapping shallow marine habitats using UAV hyperspectral imaging (the "MASSIMAL" project)
    2025
  • Martin Hansen Skjelvareid :
    MassiPipe - a data processing pipeline for hyperspectral images
    2025 DATA
  • Martin Hansen Skjelvareid :
    Massimal GitHub repository
    2025 DATA
  • Martin Skjelvareid, Eli Rinde, Kasper Hancke, Katalin Blix, Galice Guillaume Hoarau, Maia Røst Kile :
    MASSIMAL: A multimodal dataset for coastal habitat mapping in Norway
    2025 PROSJEKT / DATA / OMTALE
  • Katalin Blix, Jorge García-Jimenez, Ana Belén Ruescas, Julia Amoros, Galice Guillaume Hoarau, Eli Rinde et al.:
    Comparison of Explainable Machine Learning Methods for Marine Vegetation Mapping by Using Hyperspectral Imagery
    2024
  • Martin Hansen Skjelvareid, Eli Rinde, Kasper Hancke, Katalin Blix, Galice Guillaume Hoarau :
    The MASSIMAL dataset: High-resolution UAV hyperspectral images of shallow-water habitats with ground truth observations and annotations
    2024
  • Martin Hansen Skjelvareid :
    Kartlegging av gruntvannsområder i kystsonen: Bruk av droner, hyperspektral avbildning og innsamling av store bakkesannhets-datasett
    2024
  • Martin Hansen Skjelvareid, Eli Rinde, Kasper Hancke, Maia Røst Kile, Galice Guillaume Hoarau, Katalin Blix :
    Mapping shallow-water maerl beds with UAV hyperspectral imaging - using convolutional neural nets for image segmentation based on both spectra and texture
    2024
  • Martin Hansen Skjelvareid :
    Å kartlegge havets blå skoger med droner - Kartlegging av tang, tare og sjøgress med hyperspektral avbildning og maskinlæring
    2023
  • Martin Hansen Skjelvareid, Eli Rinde, Katalin Blix, Kasper Hancke, Galice Guillaume Hoarau :
    Mapping marine macroalgae using UAV hyperspectral imaging and machine learning
    2023
  • Martin Hansen Skjelvareid :
    Å kartlegge havets blå skoger
    2023 OMTALE
  • Martin Skjelvareid, Katalin Blix, Galice Guillaume Hoarau, Eli Rinde, Kasper Hancke :
    Mapping seagrass and rockweed habitats using UAV hyperspectral imaging and machine learning.
    2023 SAMMENDRAG
  • Martin Skjelvareid, Katalin Blix, Eli Rinde, Kasper Hancke, Galice Guillaume Hoarau :
    Shallow water habitat mapping using UAV hyperspectral imaging
    2023
  • Martin Hansen Skjelvareid, Eli Rinde, Katalin Blix, Kasper Hancke, Galice Guillaume Hoarau :
    Mapping marine macroalgae along the Norwegian coast using hyperspectral UAV imaging and convolutional nets for semantic segmentation
    2023
  • Martin Skjelvareid :
    Droner i fjæra: Nye verktøy for å kartlegge tareskog, kråkebollebeiting og ruglbunn
    2022
  • Martin Skjelvareid :
    Presentasjon av Massimal-prosjektet på "Åpen Bukt" (del av Forskningsdagene 2022)
    2022
  • Martin Skjelvareid :
    "Pitch" av Massimal-prosjektet for NRK (del av felles "digital pitchedag" for alle universiteter i Norge)
    03. November 2022
  • Silje Grue, Katalin Blix, Martin Skjelvareid :
    Machine Learning for Classifying Marine Vegetation from Hyperspectral Drone Data in the Norwegian coast
    UiT Norges arktiske universitet 2022 FULLTEKST
  • Martin Skjelvareid, Galice Guillaume Hoarau, Eli Rinde, Kasper Hancke, Katalin Blix :
    Underwater vegetation mapping based on UAV hyperspectral imaging - a potential use case for semantic segmentation through deep learning
    2022
  • Silje Grue, Martin Skjelvareid, Katalin Blix :
    Machine Learning for Classifying Marine Vegetation from Hyperspectral Drone Data in the Norwegian coast
    2022
  • Martin Hansen Skjelvareid :
    Update from the MASSIMAL project: The use of hyperspectral imaging for marine habitat mapping
    2021
  • Espen Viklem Eidum, Martin Hansen Skjelvareid :
    Flyr høyt for å kartlegge undervannsvegetasjon
    26. February 2020 FULLTEKST
  • Hilde-Gunn Bye, Martin Hansen Skjelvareid, Galice Guillaume Hoarau :
    Millioner i støtte til havforskning: - Forskning på havet, og det som er i havet, er kjempeviktig for at vi skal kunne utvikle oss fremover
    25. February 2020 FULLTEKST
  • Svein-Arnt Eriksen, Martin Hansen Skjelvareid, Galice Guillaume Hoarau :
    Banebrytende forskning for et rent og rikt hav
    27. February 2020 FULLTEKST
  • Martin Hansen Skjelvareid :
    Presentasjon av forskningsprosjektet Massimal (bidrag til Forskningsdagene 2020)
    25. September 2020 FULLTEKST
  • Martin Hansen Skjelvareid, Karsten Heia :
    Automatic quantification of gaping in fish fillets using 3D imaging – preliminary results for haddock fillets – Final report
    2018 ARKIV
  • Abdo Hassoun, Karsten Heia, Stein-Kato Lindberg, Heidi Nilsen, Martin Hansen Skjelvareid :
    Nondestructive monitoring of thermal changes in Atlantic cod (Gadus morhua) using fluorescence hyperspectral imaging
    2018 ARKIV / FULLTEKST
  • Martin Hansen Skjelvareid :
    Method development and industrial prototyping for hyperspectral imaging in the fish processing industry
    2017 OMTALE
  • Karsten Heia, Kathryn Elizabeth Washburn, Martin Hansen Skjelvareid :
    Hyperspectral Imaging applied in the food industry: Instrumentation, applications and data analysis
    2017 OMTALE
  • Kathryn Elizabeth Washburn, Svein Kristian Stormo, Martin Hansen Skjelvareid, Karsten Heia :
    Evaluating the freeze-thaw history of cod using hyperspectral imaging
    2017
  • Martin Hansen Skjelvareid :
    Hyperspektral avbildning
    2017
  • Martin Hansen Skjelvareid :
    Spectroscopic measurements of lipid content in entrails of snowcrab (Chionoecetes opilio)
    2017
  • Karsten Heia, Kathryn Elizabeth Washburn, Martin Hansen Skjelvareid :
    Automatic quality control of internal defects in cod - results from hyperspectral, ultrasound and X-ray imaging
    2017 ARKIV
  • Torstein Skåra, Svein Kristian Stormo, Dagbjørn Skipnes, Martin Hansen Skjelvareid :
    Effect of salt content and temperature on the cook loss of fresh cod
    2016
  • Svein Kristian Stormo, Torstein Skåra, Martin Hansen Skjelvareid, Karsten Heia, Dagbjørn Skipnes :
    The impact of freezing, frozen storage and thawing on a high quality product
    2016
  • Martin Hansen Skjelvareid, Mette Serine Wesmajervi Breiland, Astrid Buran Holan, Atle Mortensen :
    Effekt av ultralyd på lakselus - Resultater fra smitteforsøk med lakselus i kar
    2016 FULLTEKST
  • Martin Hansen Skjelvareid, Atle Mortensen :
    Mulig bruk av ultralyd for å forhindre eller fjerne lakselus - kunnskapsstatus per 2016
    2016
  • Grete Elisabeth Lorentzen, Karsten Heia, Martin Hansen Skjelvareid, Per Lea, Mats Carlehög :
    Holdbarhet på klippfisk Langtidslagring av klippfisk – kartlegging av kvalitetsegenskaper (AP3)
    2016 ARKIV
  • Torbjørn Tobiassen, Karsten Heia, Stein Harris Olsen, Ragnhild Aven Svalheim, Sjurdur Joensen, Kine Mari Karlsen et al.:
    Bløgging og holdbarhet på torsk
    2016 ARKIV
  • Karsten Heia, Jens Petter Wold, Martin Hansen Skjelvareid :
    Metoder for kvalitetsmåling på hel laks
    2016 ARKIV
  • Karsten Heia, Martin Hansen Skjelvareid, Rodrigo Gonzaléz Reboredo :
    Spectroscopic differentiation between rehydrated heavily salted cod and lightly salted cod
    2015

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    Research interests

    Hyperspectral imaging, ultrasound, machine learning, remote sensing, drones, unmanned aerial vehicles, synthetic aperture imaging

    Teaching

    Taught Subjects:

    DTE-2602 Introduction to Machine Learning and AI (2022 - 2024)
    TEK-1504 Physics (2023-2025)
    TEK-2801 Physics 2 (2022-2024)
    TEK-0513 Physics (preparatory course for engineering education) (2018-2022)

    Teaching Philosophy and Method:

    I have extensively taught using the "flipped classroom" method, where students can watch videos introducing a topic beforehand, and classroom time is used for problem-solving, either collectively or individually. In TEK-0513 Physics, I created instructional videos for the entire curriculum, totaling 160 videos. In TEK-1504 and TEK-2801, I have been the "local teacher" in Bodø, combined with instructional videos by Per Ødegaard.

    I strongly believe that teaching theoretical subjects like physics and machine learning should be linked to concrete experiences and preferably tangible objects that students can interact with in the classroom. In DTE-2602, I often organize joint walkthroughs of algorithms on the whiteboard rather than programming via a screen. In physics courses, I frequently bring physics equipment to demonstrate concepts, such as force meters, speed meters, etc.

    Researcher profile in Cristin
    ResearchGate
    ORCID: https://orcid.org/0000-0003-2103-865X

    Member of project

    Massimal    English content

    CV

    Education:

    • Master of science (electronics) at NTNU, specializing in signal processing and acoustics
    • PhD in physics at UiT the Arctic University of Norway (subject: Synthetic aperture ultrasound imaging for water pipeline assessment)

    Work experience:

    • PhD student / researcher at Breivoll Inspection Technologies, Tromsø (2008-2013)
    • Researcher at Nofima, Tromsø (2013-2018)
    • Associate professor at UiT the Arctic University of Norway (2018 ->)