• A Machine Learning-based Tool for Passive OS Fingerprinting with TCP Variant as a Novel Feature 

      Hagos, Desta Haileselassie; Yazidi, Anis; Kure, Øivind; Engelstad, Paal (IEEE Internet of Things Journal;Volume: 8, Issue: 5, Peer reviewed; Journal article, 2020-09-15)
      With the emergence of Internet of Things (IoT), securing and managing large, complex enterprise network infrastructure requires capturing and analyzing network traffic traces in real-time. An accurate passive Operating ...
    • Physiological-signal-based mental workload estimation via transfer dynamical autoencoders in a deep learning framework 

      Yin, Zhong; Zhao, Mengyuan; Zhang, Wei; Wang, Yongxiong; Wang, Yagang; Zhang, Jianhua (Neurocomputing;Volume 347, 28 June 2019, Journal article; Peer reviewed, 2019-02-19)
      Evaluating operator mental workload (MW) in human-machine systems via neurophysiological signals is crucial for preventing unpredicted operator performance degradation. However, the feature of physiological signals is ...
    • Predicting Remaining Fatigue Life of Topside Piping Using Deep Learning 

      Keprate, Arvind; Chatterjee, Supratik (International Conference on Applied Artificial Intelligence (ICAPAI);2021 International Conference on Applied Artificial Intelligence (ICAPAI), Conference object, 2021-06-29)
      Topside piping is the most commonly failed equipment in the Petroleum and Maritime industry. The prominent degradation mechanism causing piping failure is fatigue which results in unnecessary hydrocarbon release from these ...
    • Prediction of cloud fractional cover using machine learning 

      Svennevik, Hanna; Riegler, Michael A.; Hicks, Steven; Storelvmo, Trude; Hammer, Hugo L. (Big Data and Cognitive Computing;Volume 5 / Issue 4, Peer reviewed; Journal article, 2021-11-03)
      Climate change is stated as one of the largest issues of our time, resulting in many unwanted effects on life on earth. Cloud fractional cover (CFC), the portion of the sky covered by clouds, might affect global warming ...
    • Real-Time Detection of Events in Soccer Videos using 3D Convolutional Neural Networks 

      Rognved, Olav; Hicks, Steven; Lasantha Bandara Thambawita, Vajira; Stensland, Håkon Kvale; Zouganeli, Evi; Johansen, Dag; Riegler, Michael A.; Halvorsen, Pål (IEEE International Symposium on Multimedia; 2020 IEEE International Symposium on Multimedia (ISM), Chapter; Peer reviewed, 2020-01-22)
      In this paper, we present an algorithm for automatically detecting events in soccer videos using 3D convolutional neural networks. The algorithm uses a sliding window approach to scan over a given video to detect events ...
    • Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning 

      Jha, Debesh; Ali, Sharib; Tomar, Nikhil Kumar; Johansen, Håvard D.; Johansen, Dag; Rittscher, Jens; Riegler, Michael A.; Halvorsen, Pal (IEEE Access;Volume: 9, Peer reviewed; Journal article, 2021-03-04)
      Computer-aided detection, localization, and segmentation methods can help improve colonoscopy procedures. Even though many methods have been built to tackle automatic detection and segmentation of polyps, benchmarking of ...
    • SceneRecog: A Deep Learning Scene Recognition Model for Assisting Blind and Visually Impaired Navigate using Smartphones 

      Kuriakose, Bineeth; Shrestha, Raju; Sandnes, Frode Eika (IEEE International Conference on Systems, Man and Cybernetics;2021 IEEE International Conference on Systems, Man, and Cybernetics, Conference object, 2022-01-06)
      Deep learning models have recently gained popularity in the research community due to their high classification success rates. In this paper, we proposed an EfficientNet-Lite based scene recognition model for scene recognition ...
    • Semantic Analysis of Soccer News for Automatic Game EventClassification 

      Nordskog, Aanund Jupskaas; Halvorsen, Pål; Hicks, Steven; Stensland, Haakon; Hammer, Hugo Lewi; Johansen, Dag; Riegler, Michael (International Workshop on Content-Based Multimedia Indexing, CBMI; 2019 International Conference on Content-Based Multimedia Indexing (CBMI), Conference object, 2019-10-21)
      We are today overwhelmed with information, of which an important part is news. Sports news, in particular, has become very popular, where soccer makes up a big part of this coverage. For sports fans, it can be a time ...
    • Soccer athlete performance prediction using time series analysis 

      Ragab, Nourhan (ACIT;2022, Master thesis, 2022)
      Regardless of the sport you prefer, your favorite athlete has almost certainly disappointed you at some point. Did you jump to a conclusion and dismissed it as "not their day"? Or, did you consider the underlying causes for ...