Blar i SINTEF Digital på emneord "Machine learning"

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    • Anomaly Detection with Unknown Anomalies: Application to Maritime Machinery 

      Michalowska, Katarzyna; Riemer-Sørensen, Signe; Sterud, Camilla; Hjellset, Ole Magnus (Peer reviewed; Journal article, 2021)
      We present a framework for deriving anomaly detection algorithms on timeseries data when the time and expression of anomalous behaviour is unknown. The framework is suited for problems in which individual machine learning ...

    • Applying Object Detection to Marine Data and Exploring Explainability of a Fully Convolutional Neural Network Using Principal Component Analysis 

      Stavelin, Peter Herman; Rasheed, Adil; San, Omer; Hestnes, Arne Johan (Peer reviewed; Journal article, 2021)
      With the rise of focus on man made changes to our planet and wildlife therein, more and more emphasis is put on sustainable and responsible gathering of resources. In an effort to preserve maritime wildlife the Norwegian ...

    • Classification of Individual Finger Movements from Right Hand Using fNIRS Signal 

      Khan, Haroon; Noori, Farzan Majeed; Yazidi, Anis; Uddin, Md Zia; Khan, M.N Afzal; Mirtaheri, Peyman (Peer reviewed; Journal article, 2021)
      Functional near-infrared spectroscopy (fNIRS) is a comparatively new noninvasive, portable, and easy-to-use brain imaging modality. However, complicated dexterous tasks such as individual finger-tapping, particularly using ...

    • COROID: A Crowdsourcing-based Companion Drones to Tackle Current and Future Pandemics 

      Rauniyar, Ashish; Hagos, Desta Haileselassie; Jha, Debesh; Håkegård, Jan Erik (Peer reviewed; Journal article, 2022)
      Due to the current COVID-19 virus, which has already been declared a pandemic by the World Health Organization (WHO), we are witnessing the greatest pandemic of the decade. Millions of people are being infected, resulting ...

    • Deep learning to predict power output from respiratory inductive plethysmography data 

      Husom, Erik Johannes; Bernabé, Pierre; Sen, Sagar (Peer reviewed; Journal article, 2022)
      Power output is one of the most accurate methods for measuring exercise intensity during outdoor endurance sports, since it records the actual effect of the work performed by the muscles over time. However, power meters ...

    • Improving Computer Vision-Based Perception for Collaborative Indoor Navigation 

      Ruotsalainen, Laura; Morrison, Aiden J; Makela, Maija; Rantanen, Jesperi; Sokolova, Nadezda (Peer reviewed; Journal article, 2021)
      Collaborative navigation is the most promising technique for infrastructure-free indoor navigation for a group of pedestrians, such as rescue personnel. Infrastructure-free navigation means using a system that is able to ...

    • An Intelligent Real-Time Edge Processing Maintenance System for Industrial Manufacturing, Control, and Diagnostic 

      Vermesan, Ovidiu; Coppola, Marcello; Bahr, Roy; Bellmann, Ronnie Otto; Martinsen, Jøran Edell; Kristoffersen, Anders; Hjertaker, Torgeir; Breiland, John; Andersen, Karl; Sand, Hans Erik; Lindberg, David (Peer reviewed; Journal article, 2022)
      This paper presents an artificial intelligence (AI) based edge processing real-time maintenance system for the purposes of industrial manufacturing control and diagnostics. The system is evaluated in a soybean processing ...

    • Lessons for Data-Driven Modelling from Harmonics in the Norwegian Grid 

      Hoffmann, Volker; Torsæter, Bendik Nybakk; Rosenlund, Gjert Hovland; Andresen, Christian Andre (Peer reviewed; Journal article, 2022)
      With the advancing integration of fluctuating renewables, a more dynamic demand-side, and a grid running closer to its operational limits, future power system operators require new tools to anticipate unwanted events. ...

    • Machine Learning for Identifying Group Trajectory Outliers 

      Belhadi, Asma; Djenouri, Youcef; Djenouri, Djamel; Michalak, Tomasz; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      Prior works on the trajectory outlier detection problem solely consider individual outliers. However, in real-world scenarios, trajectory outliers can often appear in groups, e.g., a group of bikes that deviates to the ...

    • NEMO: Internet of Things based Real-time Noise and Emissions MOnitoring System for Smart Cities 

      Rauniyar, Ashish; Berge, Truls Svenn; Håkegård, Jan Erik (Peer reviewed; Journal article, 2022)
      With the advent of ubiquitous sensors and Internet of Things (IoT) applications, research and development initiatives on smart cities are ramping up worldwide. It enables remote monitoring, management, and control of devices ...

    • A tree based classifier for transient stability prediction following island splitting 

      Kiel, Erlend Sandø; Jakobsen, Sigurd Hofsmo; Haugen, Eirik; Lundemo, Sondre Duna; Riemer-Sørensen, Signe; Remonato, Filippo (Chapter, 2022)
      An unexpected failure or outage of one or multiple system components can cause a new operational situation that requires remedial actions. An important remedial action to model correctly is islanding. Finding the transient ...

    • Video Analytics in Elite Soccer: A Distributed Computing Perspective 

      Jha, Debesh; Rauniyar, Ashish; Johansen, Håvard D.; Johansen, Dag; Riegler, Michael Alexander; Halvorsen, Pål; Bagci, Ulas (Peer reviewed; Journal article, 2022)
      Ubiquitous sensors and Internet of Things (IoT)technologies have revolutionized the sports industry, providing new methodologies for planning, effective coordination of training, and match analysis post-game. New methods, ...