Viser treff 21-40 av 279

    • Universally Designed Augmented Reality (AR) for the School of the Future 

      Simon-Liedtke, Joschua Thomas; Halbach, Till (Chapter, 2023)
      Augmented Reality (AR), together with other technologies collectively referred to as eXtended Reality (XR), can offer opportunities in education for experiential learning and the visualization of abstract concepts. However, ...
    • Using stochastic simulation modelling to study occupancy levels of decentralised admission avoidance units in Norway 

      Kakad, Meetali; Utley, Martin; Dahl, Fredrik Andreas (Journal article; Peer reviewed, 2023)
      Identifying alternatives to acute hospital admission is a priority for many countries. Over 200 decentralised municipal acute units (MAUs) were established in Norway to divert low-acuity patients away from hospitals. MAUs ...
    • A Contextually Supported Abnormality Detector for Maritime Trajectories 

      Olesen, Kristoffer Vinther; Boubekki, Ahcene; Kampffmeyer, Michael Christian; Jenssen, Robert; Christensen, Anders Nymark; Hørlück, Sune; Clemmensen, Line H. (Journal article; Peer reviewed, 2023)
      The analysis of maritime traffic patterns for safety and security purposes is increasing in importance and, hence, Vessel Traffic Service operators need efficient and contextualized tools for the detection of abnormal ...
    • Discriminative multimodal learning via conditional priors in generative models 

      Andrade Mancisidor, Rogelio; Kampffmeyer, Michael Christian; Aas, Kjersti; Jenssen, Robert (Journal article; Peer reviewed, 2023)
      Deep generative models with latent variables have been used lately to learn joint representations and generative processes from multi-modal data, which depict an object from different viewpoints. These two learning mechanisms ...
    • Retrieval-Augmented Neural Response Generation Using Logical Reasoning and Relevance Scoring 

      Walker, Nicholas Thomas; Ultes, Stephan; Lison, Pierre (Journal article; Peer reviewed, 2023)
      Constructing responses in task-oriented dialogue systems typically relies on information sources such the current dialogue state or external databases. This paper presents a novel approach to knowledge-grounded response ...
    • Transparency in App Analytics: Analyzing the Collection of User Interaction Data 

      Tang, Feiyang; Østvold, Bjarte Mayanja (Chapter, 2023)
    • E-privacy concerns: A facet theoretical approach 

      Bøhm, Gisela Petra; Pfister, Hans-Rudiger; Pereira, Vanessa Ayres; Tjøstheim, Ingvar (Journal article; Peer reviewed, 2023)
    • Yield predictions of timothy (Phleum pratense L.) in Norway under future climate scenarios 

      Hellton, Kristoffer Herland; Amdahl, Helga; Thorarinsdottir, Thordis; Alsheikh, Muath K; Aamlid, Trygve S.; Jørgensen, Marit; Dalmannsdottir, Sigridur; Rognli, Odd Arne (Journal article; Peer reviewed, 2023)
      The perennial forage grass timothy (Phleum pratense L.) is the most important forage crop in Norway. Future changes in the climate will affect growing conditions and hence the yield output. We used data from the Norwegian ...
    • HIØF Easy Navigator: An Augmented Reality App Which Guides a User to Reach Their Destination 

      Safayet, Anowar; Mahta, Moezzi; Mohaiminul, Islam; Pritam, Das; Torrado, Juan Carlos (Journal article; Peer reviewed, 2023)
      New students often have trouble finding classrooms, laboratories, libraries, or other places inside a new study place. At Østfold University Col lege (HIØF), they provide paper maps to the students to find locations inside ...
    • R2030: Digitaliseringsvennlig regelverk. Metoder for regelverksforenkling, med eksempler fra bruksforskriften 

      Stolpe, Audun; Kristoffersen, Thor O.; Østvold, Bjarte M. (NR-notat;, Research report, 2023)
      Digitalisering av regelverk gir effektiviseringsgevinster gjennom utvikling av digitale tjenester. For at et regelverk skal kunne digitaliseres effektivt, er det viktig å sørge for at reglene er så enkle som mulige og at ...
    • Automatic identification of chemical moieties 

      Lederer, Jonas; Gastegger, Michael; Schütt, Kristof T.; Kampffmeyer, Michael Christian; Müller, Klaus-Robert; Unke, Oliver T. (Journal article; Peer reviewed, 2023)
      In recent years, the prediction of quantum mechanical observables with machine learning methods has become increasingly popular. Message-passing neural networks (MPNNs) solve this task by constructing atomic representations, ...
    • Statistical Embedding: Beyond Principal Components 

      Tjøstheim, Dag Bjarne; Jullum, Martin; Løland, Anders (Journal article; Peer reviewed, 2023)
      There has been an intense recent activity in embedding of very high-dimensional and nonlinear data structures, much of it in the data science and machine learning literature. We survey this activity in four parts. In the ...
    • Some recent trends in embeddings of time series and dynamic networks 

      Tjøstheim, Dag Bjarne; Jullum, Martin; Løland, Anders (Journal article; Peer reviewed, 2023)
      We give a review of some recent developments in embeddings of time series and dynamic networks. We start out with traditional principal components and then look at extensions to dynamic factor models for time series. Unlike ...
    • Earthquake Catalog Processing and Swarm Identification for the Pacific Northwest 

      Schneider, Max; Flury, Hank; Guttorp, Peter; Wright, Amy (Journal article; Peer reviewed, 2023)
      The Pacific Northwest (PNW) of North America encompasses diverse tectonic settings that can produce damaging earthquakes near population centers. Seismicity in this region is often clustered into aftershock sequences and ...
    • Evidence in the fog – Triage in fog computing systems 

      Sandvik, Jens-Petter; Franke, Katrin; Abie, Habtamu; Årnes, Andre (Journal article; Peer reviewed, 2023)
      Fog computing promises improved service scalability and lower latency for IoT systems. The concept closes the gap between full computing capabilities at the network's edge and cloud systems' centrally located processing ...
    • View it like a radiologist: Shifted windows for deep learning augmentation of CT images 

      Østmo, Eirik Agnalt; Wickstrøm, Kristoffer; Radiya, Keyur; Kampffmeyer, Michael; Jenssen, Robert (Journal article; Peer reviewed, 2023)
      Deep learning has the potential to revolutionize medical practice by automating and performing important tasks like detecting and delineating the size and locations of cancers in medical images. However, most deep learning ...
    • eXplego: An interactive Tool that Helps you Select Appropriate XAI-methods for your Explainability Needs 

      Jullum, Martin; Sjødin, Jacob; Prabhu, Robindra; Løland, Anders (Journal article; Peer reviewed, 2023)
      The growing demand for transparency, interpretability, and explainability of machine learning models and AI systems has fueled the development of methods aimed at understanding the properties and behavior of such models ...
    • Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy 

      Wickstrøm, Kristoffer Knutsen; Løkse, Sigurd Eivindson; Kampffmeyer, Michael Christian; Yu, Shujian; Príncipe, José C.; Jenssen, Robert (Journal article; Peer reviewed, 2023)
    • Recommendations for quantitative uncertainty consideration in ecology and evolution 

      Simmonds, Emily Grace; Adjei, Kwaku Peprah; Cretois, Benjamin; Dickel, Lisa; González-Gil, Ricardo; Laverick, Jack H; Mandeville, Caitlin Marie; Mandeville, Elisabeth G.; Ovaskainen, Otso Tapio; Sicacha Parada, Jorge Armando; Skarstein, Emma; O'Hara, Robert (Journal article; Peer reviewed, 2023)
      Correct quantification and reporting of model uncertainties are fundamental to reliable science. Failing to fully account for uncertainty in scientific work leads to overconfidence and potentially adverse actions. Despite ...
    • Privacy-preserving continuous authentication using behavioral biometrics 

      Baig, Ahmed Fraz; Eskeland, Sigurd; Yang, Bian (Journal article; Peer reviewed, 2023)
      Continuous authentication modalities collect and utilize users’ sensitive data to authenticate them continuously. Such data contain information about user activities, behaviors, and other demographic information, which ...