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Bilde av Nordmo, Tor-Arne Schmidt
Bilde av Nordmo, Tor-Arne Schmidt
Associate Professor Department of Computer Science tor-arne.s.nordmo@uit.no +4777644125 You can find me here

Tor-Arne Schmidt Nordmo

  • Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Håvard Dagenborg, Pål Halvorsen, Michael Alexander Riegler, Dag Johansen :
    Fishing Trawler Event Detection: An Important Step Towards Digitization of Sustainable Fishing
    IEEE conference proceedings 2023 ARKIV / DOI
  • Tor-Arne Schmidt Nordmo, Michael Riegler, Håvard Johansen Dagenborg, Dag Johansen :
    Arctic HARE: A Machine Learning-Based System for Performance Analysis of Cross-Country Skiers
    Springer 2023 ARKIV / DOI
  • Enrico Tedeschi, Tor-Arne Schmidt Nordmo, Dag Johansen, Håvard D. Johansen :
    On Optimizing Transaction Fees in Bitcoin using AI: Investigation on Miners Inclusion Pattern
    ACM Transactions on Internet Technology 2022 ARKIV / DOI
  • Tor-Arne Schmidt Nordmo, Ove Kvalsvik, Svein Ove Kvalsund, Birte Hansen, Pål Halvorsen, Steven Hicks et al.:
    FishAI: Sustainable Commercial Fishing Challenge
    Nordic Machine Intelligence (NMI) 2022 ARKIV / DOI
  • Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Bjørn Aslak Juliussen, Steven Hicks, Vajira L B Thambawita, Håvard D. Johansen et al.:
    Njord: a fishing trawler dataset
    ACM Publications 2022 ARKIV / DOI
  • André Pedersen, Erik Smistad, Tor Vikan Rise, Vibeke Grotnes Dale, Henrik P Sahlin Pettersen, Tor-Arne Schmidt Nordmo et al.:
    H2G-Net: A multi-resolution refinement approach for segmentation of breast cancer region in gigapixel histopathological images
    Frontiers in medicine 2022 ARKIV / DOI
  • Joakim Aalstad Alslie, Aril Bernhard Ovesen, Tor-Arne Schmidt Nordmo, Håvard D. Johansen, Pål Halvorsen, Michael Riegler et al.:
    Áika: A Distributed Edge System for AI Inference
    Big Data and Cognitive Computing 2022 ARKIV / DOI
  • Tor-Arne Schmidt Nordmo, Martine Espeseth, Bjørn Aslak Juliussen, Michael Alexander Riegler, Dag Johansen :
    Detection of Commercial Fishing-related Slipping Events using Multimodal Data
    IEEE (Institute of Electrical and Electronics Engineers) 2022 DOI
  • Aril Bernhard Ovesen, Tor-Arne Schmidt Nordmo, Håvard D. Johansen, Michael Alexander Riegler, Pål Halvorsen, Dag Johansen :
    File system support for privacy-preserving analysis and forensics in low-bandwidth edge environments
    Information 2021 ARKIV / DOI
  • Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Håvard D. Johansen, Michael Alexander Riegler, Pål Halvorsen, Dag Johansen :
    Dutkat: A Multimedia System for Catching Illegal Catchers in a Privacy-Preserving Manner
    ACM Digital Library 2021 DOI
  • Enrico Tedeschi, Tor-Arne Schmidt Nordmo, Dag Johansen, Håvard D. Johansen :
    Predicting Transaction Latency with Deep Learning in Proof-of-Work Blockchains
    IEEE International Conference on Big Data and Smart Computing 07. December 2019 DATA / ARKIV / DOI
  • Tor-Arne Schmidt Nordmo :
    Dutkat - A Privacy-Preserving Edge-based System for Automatic Catch Documentation and Detection of Illegal Events
    UiT Norges arktiske universitet 2023
  • Tor-Arne Schmidt Nordmo :
    Dutkat - A Privacy-Preserving Edge-based System for Automatic Catch Documentation and Detection of Illegal Events
    2023
  • Tor-Arne Schmidt Nordmo :
    Presentasjon av eget arbeid for journalister
    2023
  • Tor-Arne Schmidt Nordmo :
    Maritime Internet of Things - Architecture and machine learning techniques for ship intelligent decision support systems
    2023
  • Tor-Arne Schmidt Nordmo :
    Utdanning og KI
    2023
  • Tor-Arne Schmidt Nordmo :
    Arctic HARE: A Machine Learning-Based System for Performance Analysis of Cross-Country Skiers
    2023
  • Aril Bernhard Ovesen, Tor-Arne Schmidt Nordmo, Dag Johansen :
    Compliant multimedia storage and data extraction from the untrusted and privacy-sensitive edge
    2023
  • Tor-Arne Schmidt Nordmo :
    Introduksjon til KI
    2023
  • Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Bjørn Aslak Juliussen, Steven A. Hicks, Vajira Thambawita, Håvard D. Johansen et al.:
    Njord: A Fishing Trawler Dataset
    2022
  • Michael Alexander Riegler, Dag Johansen, Bjørn Aslak Juliussen, Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Pål Halvorsen et al.:
    Njord: An out-in-the-wild real world fish vessel catch analysis dataset
    2022
  • Håvard D. Johansen, Dag Johansen, Bjørn Aslak Juliussen, Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Pål Halvorsen et al.:
    Sustainable commercial fishing: Digital inspectors to the rescue
    2022
  • Michael Alexander Riegler, Dag Johansen, Bjørn Aslak Juliussen, Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Pål Halvorsen et al.:
    Njord: An out-in-the-wild real world fish vessel catch analysis dataset
    Arctic Frontiers : Abstracts 2022
  • Dag Johansen, Bjørn Aslak Juliussen, Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Pål Halvorsen, Håvard D. Johansen et al.:
    Sustainable commercial fishing: Digital inspectors to the rescue
    Arctic Frontiers : Abstracts 2022
  • Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Bjørn Aslak Juliussen, Steven A. Hicks, Vajira Thambawita, Håvard D. Johansen et al.:
    Njord: A Fishing Trawler Dataset
    2022
  • Tor-Arne Schmidt Nordmo, Ove Kvalsvik, Svein Ove Kvalsund, Birte Hansen, Pål Halvorsen, Steven Hicks et al.:
    FishAI: Sustainable Commercial Fishing Challenge
    Nordic Machine Intelligence (NMI) 2022 DOI
  • Enrico Tedeschi, Tor-Arne Schmidt Nordmo, Dag Johansen, Håvard D. Johansen :
    Predicting Transaction Latency with Deep Learning in Proof-of-Work Blockchains
    2019
  • Tor-Arne Schmidt Nordmo, Robert Pettersen, Dag Johansen :
    Arctic HARE - Poster
    2018

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    Research interests

    Artificial Intelligence

    Teaching

    INF-2600 Artificial Intelligence, Methods and Applications (Course Manager and Lecturer)

    INF-1600 Introduction to Artificial Intelligence (Course Manager and Lecturer)

    Researcher profile in Cristin
    ResearchGate

    Member of research group

    Cyber Security Group (CSG)   English content

    Member of project

    Edge Computing Sports Technology Systems Support for AI