Nye registreringer

  • Software startups-A research agenda 

    Unterkalmsteiner, Michael; Abrahamsson, Pekka Kalevi; Wang, Xiaofeng; Nguyen-Duc, Anh; Shah, Syed; Bajwa, Sohaib Shahid; Baltes, Guido H; Conboy, Kieran; Cullina, Eoin; Dennehy, Denis; Edison, Henry; Fernandez-Sanchez, Carlos; Garbajosa, Juan; Gorschek, Tony; Klotins, Eriks; Hokkanen, Laura; Kon, Fabio; Lunesu, Ilaria; Marchesi, Michele; Morgan, Lorraine; Oivo, Markku; Selig, Christoph; Seppänen, Pertti; Sweetman, Roger; Tyrväinen, Pasi; Ungerer, Christina; Yague, Agustin (Peer reviewed; Journal article, 2016)
    Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models. Softwarestartups are quite distinct from ...
  • Nearest Neighbor Query Processing in Spatial and Spatio-Temporal Databases 

    Markussen, Markus (Master thesis, 2020)
    I disse dager produserer vi enorme mengder data, mer spesifikt stedfestet data, og behovet for raske indekseringsmetoder er avgjørende for hvordan vi får tilgang til denne dataen. I dag bruker de fleste databasesystemene ...
  • Digital Service Outsourcing Through Sociotechnical Transformation 

    Helgesen, Trine-Lise (Master thesis, 2020)
    Industirer I dag blir møtt av et fort marked for digitale tjenester tilbudt av IT selskaper, og gjennom den digitale æra utvalget av tjenester har økt som følger av konstant innovasjon. Men ettersom den integrerte teknologien ...
  • Convolutional Neural Networks for Part-of-Speech Tagging 

    Stavland, Stine S. (Master thesis, 2020)
    Konvolusjonelle nevrale nettverk har vanligvis ikke vært brukt til sekvensprosesseringsoppgaver, men nylige forskningsarbeid har gitt inspirasjon til å teste ut bruk av konvolusjonelle nevrale nettverk for ordklassemerking. ...
  • Generating Novel Compounds in Technical Translations 

    Orvedal, Maren Helene (Master thesis, 2020)
    Samansetjingar er leksem som er samansette av fleire ledd. Prinsipielt sett er det mogleg å forme eit uendeleg antal samansette ord, og det er derfor umogleg å ramsa opp alle moglege samansetjingar i eit leksikon. Når ein ...
  • Evolving Multi-Spatial-Substrates to extend HyperNEAT in order to increase Functional Modularity 

    Stensbye, Andreas Røyset (Master thesis, 2019)
    Humanity have begun to actively use artificial intelligence to solve problems. However, many of these solutions are time consuming to develop and often fine-tuned to specific problems. With the world in constant change, ...
  • Automatic updating of histograms in MySQL 

    Vestrheim, Sevre (Master thesis, 2019)
    Når en spørring blir optimalisert av spørreoptimalisatoren i en database er det mange faktorer som undersøkes før valg av spørreplan blir tatt. En av disse er rekkefølgen tabeller joines i. Rekkefølgen bestemmes i stor ...
  • Exploring the viability of a CRDT-based Data Model for a distributed decision support system 

    Holme, Jarl (Master thesis, 2020)
    Konfliktfrie replikerte datastrukturer (CRDT-er) forsikrer at endringer utført i parallell resulterer i identiske strukturer som gjør at de konseptuelt kan brukes til å implementere et distribuert system som ikke begrenser ...
  • Gjenfinning av sau ved hjelp av drone 

    Guttormsen, Magnus (Master thesis, 2019)
    Hver høst må sauebønner over hele Norge hente inn sauene som har vært på beite. Dette er en tidkrevende prosess hvor de får hjelp av familie, venner og turgåere for å lokalisere og drive sauen til gården. Lokalisering ...
  • A Metrological Measurement of Texture in Hyperspectral Images Using Relocated Spectral Difference Occurrence Matrix 

    Chu, Rui Jian; Richard, Noel; Fernandez-Maloigne, Christine; Hardeberg, Jon Yngve (Peer reviewed; Journal article, 2019)
    A new hyperspectral texture descriptor, Relocated Spectral Difference Occurrence Matrix (rSDOM) is proposed. It assesses the distribution of spectral difference in a given neighborhood. For metrological purposes, rSDOM ...
  • Deep Learning Approaches for Whiteboard Image Quality Enhancement 

    Abebe, Mekides Assefa; Hardeberg, Jon Yngve (Peer reviewed; Journal article, 2019)
    Different whiteboard image degradations highly reduce the legibility of pen-stroke content as well as the overall quality of the images. Consequently, different researchers addressed the problem through different image ...
  • Evaluating the naturalness and legibility of whiteboard image enhancements 

    Abebe, Mekides Assefa; Hardeberg, Jon Yngve (Peer reviewed; Journal article, 2019)
    Over the years, there have been many studies conducted for whiteboard image detection, extraction and quality enhancements. However, the image quality attributes of the streaming whiteboard contents as well as users’ ...
  • A case‑based reasoning recommender system for sustainable smart city development 

    Bokolo, Anthony Junior (Peer reviewed; Journal article, 2020)
    With the deployment of information and communication technologies (ICTs) and the needs of data and information sharing within cities, smart city aims to provide value-added services to improve citizens’ quality of life. ...
  • Out-of-the-Box Reproducibility: A Survey of Machine Learning Platforms 

    Isdahl, Richard Juul; Gundersen, Odd Erik (Chapter, 2019)
    Even machine learning experiments that are fully conducted on computers are not necessarily reproducible. An increasing number of open source and commercial, closed source machine learning platforms are being developed ...
  • Appearance perception of textiles: a tactile and visual texture study 

    Mirjalili, Fereshteh; Hardeberg, Jon Yngve (Peer reviewed; Journal article, 2019)
    Texture analysis and characterization based on human perception has been continuously sought after by psychology and computer vision researchers. However, the fundamental question of how humans truly perceive texture still ...
  • A Metrological Framework for Hyperspectral Texture Analysis Using Relative Spectral Difference Occurrence Matrix 

    Chu, Rui Jian; Richard, Noel; Ghorbel, Faouzi; Fernandez-Maloigne, Christine; Hardeberg, Jon Yngve (Peer reviewed; Journal article, 2019)
    A new hyperspectral texture descriptor, Relative Spectral Difference Occurrence Matrix (RSDOM) is proposed. Developed in a metrological framework, it simultaneously considers the distribution of spectra and their spatial ...
  • Amplified locality‐sensitive hashing‐based recommender systems with privacy protection 

    Chi, Xiaoxiao; Yan, Chao; Wang, Hao; Rafique, Wajid; Qi, Lianyong (Peer reviewed; Journal article, 2020)
    With the advent of Internet of Things (IoT) age, the variety and volume of web services have been increasing at a fast speed. This often leads to users' selections for web services more complicated. Under the circumstance, ...
  • Dimensionality reduction and visualisation of hyperspectral ink data using t-SNE 

    Melit Devassy, Binu; George, Sony (Peer reviewed; Journal article, 2020)
    Ink analysis is an important tool in forensic science and document analysis. Hyperspectral imaging (HSI) captures large number of narrowband images across the electromagnetic spectrum. HSI is one of the non-invasive tools ...
  • Exploring the Role of Large Centralised Caches in Thermal Efficient Chip Design 

    Chakraborty, Shounak; Kapoor, Hemangee K (Peer reviewed; Journal article, 2019)
    In the era of short channel length, Dynamic Thermal Management (DTM) has become a challenging task for the architects and designers engineering modern Chip Multi-Processors (CMPs). Ever-increasing demand of processing power ...
  • Similarity measure development for case-based reasoning?a data-driven approach 

    Verma, Deepika; Bach, Kerstin; Mork, Paul Jarle (Peer reviewed; Journal article, 2019)
    In this paper, we demonstrate a data-driven methodology for modelling the local similarity measures of various attributes in a dataset. We analyse the spread in the numerical attributes and estimate their distribution using ...

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