• Deep learning based hashtag recommendation system for multimedia data 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      This work aims to provide a novel hybrid architecture to suggest appropriate hashtags to a collection of orpheline tweets. The methodology starts with defining the collection of batches used in the convolutional neural ...
    • Deep learning for image-based liver analysis — A comprehensive review focusing on malignant lesions 

      Survarachakan, Shanmugapriya; Prasad, Pravda Jith Ray; Naseem, Rabia; Perez de Frutos, Javier; Kumar, Rahul Prasanna; Langø, Thomas; Alaya Cheikh, Faouzi; Elle, Ole Jakob; Lindseth, Frank (Peer reviewed; Journal article, 2022)
      Deep learning-based methods, in particular, convolutional neural networks and fully convolutional networks are now widely used in the medical image analysis domain. The scope of this review focuses on the analysis using ...
    • Deep Learning for Improved Precision and Reproducibility of Left Ventricular Strain in Echocardiography: A Test-Retest Study 

      Salte, Ivar Mjåland; Østvik, Andreas; Olaisen, Sindre Hellum; Karlsen, Sigve; Dahlslett, Thomas; Smistad, Erik; Eriksen-Volnes, Torfinn Kirknes; Brunvand, Harald; Haugaa, Kristina Ingrid Helena Hermann; Edvardsen, Thor; Dalen, Håvard; Løvstakken, Lasse; Grenne, Bjørnar Leangen (Peer reviewed; Journal article, 2023)
      Aims: Assessment of left ventricular (LV) function by echocardiography is hampered by modest test-retest reproducibility. A novel artificial intelligence (AI) method based on deep learning provides fully automated measurements ...
    • Deep learning for pedestrian collective behavior analysis in smart cities: A model of group trajectory outlier detection 

      Belhadi, Asma; Djenouri, Youcef; Srivastava, Gautam; Djenouri, Djamel; Lin, Jerry Chun-Wei; Fortino, Giancarlo (Peer reviewed; Journal article, 2021)
      This paper introduces a new model to identify collective abnormal human behaviors from large pedestrian data in smart cities. To accurately solve the problem, several algorithms have been proposed in this paper. These can ...
    • Deep learning for prediction of depressive symptoms in a large textual dataset 

      Uddin, Md Zia; Dysthe, Kim Kristoffer; Følstad, Asbjørn; Brandtzæg, Petter Bae (Peer reviewed; Journal article, 2021)
      Depression is a common illness worldwide with potentially severe implications. Early identification of depressive symptoms is a crucial first step towards assessment, intervention, and relapse prevention. With an increase ...
    • 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 ...
    • Deep neural network enabled corrective source term approach to hybrid analysis and modeling 

      Blakseth, Sindre Stenen; Rasheed, Adil; Kvamsdal, Trond; San, Omer (Peer reviewed; Journal article, 2022)
      In this work, we introduce, justify and demonstrate the Corrective Source Term Approach (CoSTA)—a novel approach to Hybrid Analysis and Modeling (HAM). The objective of HAM is to combine physics-based modeling (PBM) and ...
    • Deep Reinforcement Learning Attitude Control of Fixed Wing UAVs Using Proximal Policy Optimization 

      Bøhn, Eivind Eigil; Coates, Erlend Magnus Lervik; Moe, Signe; Johansen, Tor Arne (Chapter; Peer reviewed, 2019)
      Contemporary autopilot systems for unmanned aerial vehicles (UAVs) are far more limited in their flight envelope as compared to experienced human pilots, thereby restricting the conditions UAVs can operate in and the types ...
    • Defining the initial case-base for a CBR operator support system in digital finishing A methodological knowledge acquisition approach 

      Wienhofen, Leendert Wilhelmus Marinus; Mathisen, Bjørn Magnus (Journal article; Peer reviewed, 2016)
      Case-based reasoning (CBR) literature defines the process of defining a case-base as a hard and time-demanding task though the same literature does not report in detail on how to build your initial case base. The main ...
    • Definitions and Approaches to Model Quality in Model-Based Software Development – A Review of Literature 

      Mohagheghi, Parastoo; Dehlen, Vegard; Neple, Tor (Journal article; Peer reviewed, 2009)
      More attention is paid to the quality of models along with the growing importance of modelling in software development. We performed a systematic review of studies discussing model quality published since 2000 to identify ...
    • Delicar: A smart deep learning based self driving product delivery car in perspective of Bangladesh 

      Chy, Md. Kalim Amzad; Masum, Abdul Kadar Muhammad; Sayeed, Kazi Abdullah Mohammad; Uddin, Md Zia (Peer reviewed; Journal article, 2022)
      The rapid expansion of a country’s economy is highly dependent on timely product distribution, which is hampered by terrible traffic congestion. Additional staff are also required to follow the delivery vehicle while it ...
    • Deliverance from Trust through a Redundant Array of Independent Net-storages in Cloud Computing 

      Zhao, Gansen; JAATUN, Martin Gilje; Vasilakos, Athanasios; Nyre, Åsmund Ahlmann; Alapnes, Stian; Yue, Qiang; Tang, Yong (Chapter, 2011)
      Cloud storage services are gaining more and more attention. Surveys suggest that the confidentiality issue is one of the major obstacles for users to use cloud storage services to keep sensitive data. This paper proposes ...
    • Delt situasjonsforståelse under søk og redning i nordområdene 

      Haugstveit, Ida Maria; Skjetne, Jan Håvard; Walderhaug, Ståle; Antonsen, yngve; Ellingsen, May-Britt; Håheim-Saers, Nils; Heggelund, Yngve (SINTEF Rapport;, Research report, 2016)
      Prosjektets mål er å bidra til økt kunnskap om hvordan etablere delt situasjonsforståelse mellom sentrale aktører innen SAR i Nordområdet. Prosjektgruppa har arbeidet ut ifra en menneske-teknologi-organisasjon (MTO) ...
    • Demensomsorg i Trøndelag 

      Sivertsen, Håkon; Løe, Ida Camilla (SINTEF Rapport;2022:00538, Research report, 2022)
      Vi har kartlagt hvordan yngre personer med demenssykdom ivaretas i kommunene i Trøndelag, hvilken kompetanse og kapasitet de møter og hvordan kommunene arbeider. Data er samlet inn via et spørreskjema hvor 34 av 38 ...
    • Demonstrating the impact of bidirectional coupling on the performance of an ocean-met model 

      Rasheed, Adil; Süld, Jakob Kristoffer; Tabib, Mandar; Kvamsdal, Trond; Kristiansen, Jørn (Journal article; Peer reviewed, 2017)
      The mass, momentum and energy fluxes between the atmosphere and ocean surface depend on the state of the ocean surface. The fluxes in turn can significantly alter the nature of the marine boundary layer and the state of ...
    • Dependency Management in Large-Scale Agile: A Case Study of DevOps Teams 

      Stray, Viktoria; Moe, Nils Brede; Aasheim, Andreas (Proceedings of the Annual Hawaii International Conference on System Sciences (HICSS);, Chapter; Peer reviewed, 2019)
      Managing dependencies between teams and within teams is critical when running large-scale agile projects. In large-scale software development, work is carried out simultaneously by many developers and development teams. ...
    • Deployment models: Towards eliminating security concerns from cloud computing 

      Zhao, Gansen; Rong, Chunming; Jaatun, Martin Gilje; Sandnes, Frode Eika (Chapter, 2010)
      Cloud computing has become a popular choice as an alternative to investing new IT systems. When making decisions on adopting cloud computing related solutions, security has always been a major concern. This article summarizes ...
    • Describing Component Collaboration Using Goal Sequences 

      Carrez, Cyril; Floch, Jacqueline; Sanders, Richard (Journal article; Peer reviewed, 2008)
    • Describing Service Performances: What Are the Challenges? 

      Lee, Eunji (Journal article; Peer reviewed, 2017)
      To enhance operational sustainability of services, service quality is needed to be monitored. Expected and experienced service can be compared to evaluate service quality. Service performances involves a sequence of events ...
    • Desentralisert Holter - Hvordan flytte Holter-undersøkelsen fra poliklinikk til fastlegekontor? 

      Svagård, Ingrid Storruste; Ausen, Dag; Fensli, Rune Werner; Gundersen, Torstein (Research report, 2010)
      Prosjektet ”Desentralisert Holter” har utredet Holter-undersøkelsen slik de utføres i dag og identifisert og spesifisert forbedringspunkter. Utredningen er gjennomført ved Sørlandet Sykehus i Arendal og omkringliggende ...