• 3D visualization of weather forecasts and topography 

      Skotnes, Harald; Hartvigsen, Gunnar; Johansen, Dag (Research report; Forskningsrapport, 1994-09)
      Advances in computing power and graphics have increased the use of graphics in weather forecasting. This includes 3D animation sequences and geographical information systems. The paper addresses the main problems and presents preliminary results of the visualization of atmospheric models in conjunction with the underlying topography. The goal is among others to make a sort of 3D satellite pictures ...
    • Accountable Human Subject Research Data Processing using Lohpi 

      Sharma, Aakash; Bye Nilsen, Thomas; Brenna, Lars; Johansen, Dag; Johansen, Håvard D. (Conference object; Konferansebidrag, 2021-06)
      In human subject research, various data about the studied individuals are collected. Through re-identification and statistical inferences, this data can be exploited for interests other than the ones the subjects initially consented to. Such exploitation must be avoided to maintain trust with the researched population. We argue that keeping data-access policies up-to-date and building accountability ...
    • Adding mobility to non-mobile web robots 

      Sudmann, Nils P.; Johansen, Dag (Research report; Forskningsrapport, 2000)
      In this paper we will show that it is possible to combine mobile agent technology with existing non-mobile data mining applications. The motivation for this is the advantage mobile agents offer in moving the computation closer to the data in a distributed system. This can save bandwidth and increase performance when the data is condensed as a result of data mining.
    • Algorithms that forget: Machine unlearning and the right to erasure 

      Juliussen, Bjørn Aslak; Rui, Jon Petter; Johansen, Dag (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-09-22)
      rticle 17 of the General Data Protection Regulation (GDPR) contains a right for the data subject to obtain the erasure of personal data. The right to erasure in the GDPR gives, however, little clear guidance on how controllers processing personal data should erase the personal data to meet the requirements set out in Article 17. Machine Learning (ML) models that have been trained on personal data ...
    • An approach towards an agent computing environment 

      Marzullo, Keith; Johansen, Dag; Lauvset, Kåre J. (Research report; Forskningsrapport, 1998)
      We devise a mobile agent middleware architecture for supporting distributed applications in a wide-area network. The architecture provides a structural framework for functional components that are needed to support mobile agents in asymmetric networking environments.
    • Automatic thumbnail selection for soccer videos using machine learning 

      Husa, Andreas; Midoglu, Cise; Hammou, Malek; Hicks, Steven; Johansen, Dag; Kupka, Tomas; Riegler, Michael; Halvorsen, Pål (Chapter; Bokkapittel, 2022-08-05)
      Thumbnail selection is a very important aspect of online sport video presentation, as thumbnails capture the essence of important events, engage viewers, and make video clips attractive to watch. Traditional solutions in the soccer domain for presenting highlight clips of important events such as goals, substitutions, and cards rely on the manual or static selection of thumbnails. However, such ...
    • Áika: A Distributed Edge System for AI Inference 

      Alslie, Joakim Aalstad; Ovesen, Aril Bernhard; Nordmo, Tor-Arne Schmidt; Johansen, Håvard D.; Halvorsen, Pål; Riegler, Michael; Johansen, Dag (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-06-17)
      Video monitoring and surveillance of commercial fisheries in world oceans has been proposed by the governing bodies of several nations as a response to crimes such as overfishing. Traditional video monitoring systems may not be suitable due to limitations in the offshore fishing environment, including low bandwidth, unstable satellite network connections and issues of preserving the privacy of crew ...
    • Building agent applications using wrappers 

      Sudmann, Nils P.; Johansen, Dag (Research report; Forskningsrapport, 2001-01-11)
      For the past seven years, the TACOMA project has investigated software support for mobile agents. Several prototypes have been developed, with experiences in distributed applications directing the effort. This paper presents a new mechanism that supports implementing agent applications by creating troops of agents using wrappers. This solution requires little extra support from the agent system, and ...
    • Capturing Nutrition Data for Sports: Challenges and Ethical Issues 

      Sharma, Aakash; Czerwinska, Katja P; Johansen, Dag; Dagenborg, Håvard (Conference object; Konferansebidrag, 2023-01)
      Nutritionplaysakeyroleinanathlete’s performance, health, and mental well-being. Capturing nutrition data is crucial for analyzing those relations and performing necessary interventions. Using traditional methods to capture long-term nutritional data requires intensive labor, and is prone to errors and biases. Artificial Intelligence (AI) methods can be used to remedy such problems by using Image-Based ...
    • Capturing Nutrition Data for Sports: Challenges and Ethical Issues 

      Sharma, Aakash; Czerwinska, Katja P; Johansen, Dag; Dagenborg, Håvard Johansen (Chapter; Bokkapittel, 2023)
      Nutrition plays a key role in an athlete’s performance, health, and mental well-being. Capturing nutrition data is crucial for analyzing those relations and performing necessary interventions. Using traditional methods to capture long-term nutritional data requires intensive labor, and is prone to errors and biases. Artificial Intelligence (AI) methods can be used to remedy such problems by using ...
    • A comprehensive analysis of classification methods in gastrointestinal endoscopy imaging 

      Jha, Debesh; Ali, Sharib; Hicks, Steven; Thambawita, Vajira L B; Borgli, Hanna; Smedsrud, Pia H.; de Lange, Thomas; Pogorelov, Konstantin; Wang, Xiaowei; Harzig, Philipp; Tran, Minh-Triet; Meng, Wenhua; Hoang, Trung-Hieu; Dias, Danielle; Ko, Tobey H.; Agrawal, Taruna; Ostroukhova, Olga; Khan, Zeshan; Tahir, Muhammed Atif; Liu, Yang; Chang, Yuan; Kirkerød, Mathias; Johansen, Dag; Lux, Mathias; Johansen, Håvard D.; Riegler, Michael; Halvorsen, Pål (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-02-19)
      Gastrointestinal (GI) endoscopy has been an active field of research motivated by the large number of highly lethal GI cancers. Early GI cancer precursors are often missed during the endoscopic surveillance. The high missed rate of such abnormalities during endoscopy is thus a critical bottleneck. Lack of attentiveness due to tiring procedures, and requirement of training are few contributing factors. ...
    • Cooperation through information interchange in StormCast 

      Hartvigsen, Gunnar; Johansen, Dag (Research report; Forskningsrapport, 1990)
      This paper addresses the cooperation between different expert system modules in a networking environment. StormCast - a distributed artificial intelligence application for severe storm forecasting is used as a case to obtain practical results. Two key aspects is investigated, first the representation of knowledge in this kind of environment is outlined. Then the cooperating nature of a group of ...
    • Design Principles for Isolation Kernels 

      Kvalnes, Åge; Johansen, Dag; Valvåg, Steffen (Research report; Forskningsrapport, 2011)
    • Digital Chronofiles of Life Experience 

      Sødring, Thomas; Johansen, Dag; Gurrin, Cathal (Journal article; Tidsskriftartikkel; Peer reviewed, 2015)
    • Digital Chronofiles of Life Experience 

      Gurrin, Cathal; Johansen, Håvard; Sødring, Thomas; Johansen, Dag (Chapter; Bokkapittel, 2015-02-28)
      Technology has brought us to the point where we are able to digitally sample life experience in rich multimedia detail, often referred to as lifelogging. In this paper we explore the potential of lifelogging for the digitisation and archiving of life experience into a longitudinal media archive for an individual. We motivate the historical archive potential for rich digital memories, enabling ...
    • Dissecting deep neural networks for better medical image classification and classification understanding 

      Hicks, Steven Alexander; Riegler, Michael; Pogorelov, Konstantin; Ånonsen, Kim Vidar; de Lange, Thomas; Johansen, Dag; Jeppsson, Mattis; Randel, Kristin Ranheim; Eskeland, Sigrun Losada; Halvorsen, Pål (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-07-23)
      Neural networks, in the context of deep learning, show much promise in becoming an important tool with the purpose assisting medical doctors in disease detection during patient examinations. However, the current state of deep learning is something of a "black box", making it very difficult to understand what internal processes lead to a given result. This is not only true for non-technical users but ...
    • DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation 

      Jha, Debesh; Riegler, Michael Alexander; Johansen, Dag; Halvorsen, Pål; Johansen, Håvard D. (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-09-01)
      Semantic image segmentation is the process of labeling each pixel of an image with its corresponding class. An encoder-decoder based approach, like U-Net and its variants, is a popular strategy for solving medical image segmentation tasks. To improve the performance of U-Net on various segmentation tasks, we propose a novel architecture called DoubleU-Net, which is a combination of two U-Net ...
    • Dynamically loading mobile/cloud assemblies 

      Pettersen, Robert; Johansen, Håvard D.; Valvåg, Steffen Viken; Johansen, Dag (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-07-20)
      Distributed applications that span mobile devices, computing clusters, and cloud services, require robust and flexible mechanisms for dynamically loading code. This paper describes lady: a system that augments the .net platform with a highly reliable mechanism for resolving and loading assemblies, and arranges for safe execution of partially trusted code. Key benefits of lady are the low latency and ...
    • Efficient disease detection in gastrointestinal videos – global features versus neural networks 

      Pogorelov, Konstantin; Riegler, Michael; Eskeland, Sigrun Losada; de Lange, Thomas; Johansen, Dag; Griwodz, Carsten; Schmidt, Peter Thelin; Halvorsen, Pål (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-07-19)
      Analysis of medical videos from the human gastrointestinal (GI) tract for detection and localization of abnormalities like lesions and diseases requires both high precision and recall. Additionally, it is important to support efficient, real-time processing for live feedback during (i) standard colonoscopies and (ii) scalability for massive population-based screening, which we conjecture can be done ...
    • Efficient live and on-demand tiled HEVC 360 VR video streaming 

      Jeppsson, Mattis; Espeland, Håvard; Kupka, Tomas; Langseth, Ragnar; Petlund, Andreas; Peng, Qiaoqiao; Xue, Chuansong; Johansen, Dag; Pogorelov, Konstantin; Stensland, Håkon Kvale; Griwodz, Carsten; Riegler, Michael; Halvorsen, Pål (Journal article; Tidsskriftartikkel; Peer reviewed, 2019)
      360∘ panorama video displayed through Virtual Reality (VR) glasses or large screens offers immersive user experiences, but as such technology becomes commonplace, the need for efficient streaming methods of such high-bitrate videos arises. In this respect, the attention that 360∘ panorama video has received lately is huge. Many methods have already been proposed, and in this paper, we shed more light ...