• Granularity as a qualitative concept for GIR 

      Ahlers, Dirk (Chapter, 2015)
      We examine the notion of granularity for qualitative thinking about geospatial data and location references. Granularity can be understood as an abstraction of level of detail or spatial resolution. Pure coordinates, which ...
    • Graph Convolutional Networks for Predicting Cerebral Palsy in Infants 

      Haukeland, Andreas; Aubert, Sindre Aarnes (Master thesis, 2021)
    • Graph diffusion kernel LMS using random Fourier features 

      Gogineni, Vinay Chakravarthi; Elias, Vitor; Martins, Wallace; Werner, Stefan (Chapter, 2021)
      This work introduces kernel adaptive graph filters that operate in the reproducing kernel Hilbert space. We propose a centralized graph kernel least mean squares (GKLMS) approach for identifying the nonlinear graph filters. ...
    • Graph Gaussian Process Classifier with Anchor Graph and Label Propagation 

      Ovanger, Oscar (Master thesis, 2021)
      Gaussiske prosesser er en viktig metode for maskinlæring da den lar oss sette en prioritet p˚a formen til en funksjon, og den arver fine egenskaper fra normalfordelingen. Den har blitt brukt b˚ade som en regresjons- og ...
    • Graph Kernel Recursive Least-Squares Algorithms 

      Gogineni, Vinay Chakravarthi; Naumova, Valeriya; Werner, Stefan; Huang, Yih-Fang (Chapter, 2022)
      This paper presents graph kernel adaptive filters that model nonlinear input-output relationships of streaming graph signals. To this end, we propose centralized and distributed graph kernel recursive least-squares (GKRLS) ...
    • A graph neural approach for group recommendation system based on pairwise preferences 

      Abolghasemi, Roza; Viedma, Enrique Herrera; Engelstad, Paal E.; Djenouri, Youcef; Yazidi, Anis (Peer reviewed; Journal article, 2024)
      Pairwise preference information, which involves users expressing their preferences by comparing items, plays a crucial role in decision-making and has recently found application in recommendation systems. In this study, ...
    • Graph neural network-based virtual network function deployment optimization 

      Kim, Heegon; Park, Suhyun; Lange, Stanislav; Lee, Do-Young; Heo, Dongnyeong; Choi, Heeyoul; Yoo, Jae-Hyoung; Hong, James W. (Peer reviewed; Journal article, 2021)
      Software-defined networking (SDN) and network function virtualization (NFV) help reduce the operating expenditure (OPEX) and capital expenditure (CAPEX) as well as increase the network flexibility and agility. However, ...
    • Graph Representation of DNS-related Data for Detecting Malicious Actions 

      Rismyhr, Eirik (Master thesis, 2020)
      Skadevare er et økende problem innen cybersikkerhet. Forskning viser at en stor andel av skadevaren benytter seg av DNS-protokollen for å utføre ondsinnede handlinger. Da DNS-protokollen først ble utviklet var ikke sikkerhet ...
    • Graph representation of documents content and its suitability for text mining tasks 

      Viaño Iglesias, Adrian (Master thesis, 2011)
      Association rules mining is one of the the most relevant techniques of data mining. It has been also applied in the domain of text mining, but the results are hard to interpret. In this matter, an Association Network is ...
    • Graph theoretical approach to sexual predator detection 

      Matteini Palmerini, Riccardo (Master thesis, 2021)
      Med teknologispredningen er vi i stand til å komme i kontakt med venner langt unna så vel som ukjente personer. Bak skjermer kan personer med onde hensikter skjule identiteten deres og handle i frihet. Overgripere tar ...
    • Graph-based methods for data-driven reservoir modeling 

      Devold, Ingvild Strømsheim (Master thesis, 2023)
      Datadrevne metoder innen reservoarmodellering inkluderer både fullt ut databaserte maskinlæringsmetoder og historietilpasning av tradisjonelle matematiske modeller. I denne oppgaven foreslår vi en type hybride, grafbaserte ...
    • Graph-Based Multi-Modal SLAM for Resilience in Sensor-Degraded Environments 

      Totland, Sigurd Vatn (Master thesis, 2021)
      Pålitelig og nøyaktig samtidig lokalisering og kartlegging (SLAM) er en nødvendig forutsetning for vellykket bruk av autonome systemer, som gjør det mulig for roboter å kartlegge og navigere omgivelsene sine, uten bruk av ...
    • Graph-based Natural Language Processing: Graph edit distance applied to the task of detecting plagiarism 

      Røkenes, Håkon Drolsum (Master thesis, 2012)
      The focus of this thesis is the exploration of graph-based similarity, in the context of natural language processing. The work is motivated by a need for richer representations of text. A graph edit distance algorithm was ...
    • Graph-based Path Planning in a Simulated Rough Terrain 

      Jonsebråten, Andreas; Karlsen, Vegar; Varhaug, Glenn R. (Bachelor thesis, 2023)
      Denne rapporten beskriver implementasjonen av baneplanleggingsrammeverket, GBPlanner2, for en simulert versjon av Lone Wolf ATVen. Rapporten dekker også implementasjon av viapunktfunksjonalitet. Spesifikasjoner, design og ...
    • Graph-Based Representations for Textual Case-Based Reasoning 

      Valle, Kjetil (Master thesis, 2011)
      This thesis presents a graph-based approach to the problem of text representation. The work is motivated by the need for better representations for use in textual Case-Based Reasoning (CBR). In CBR new problems are solved ...
    • Graph-based slam and navigation in a simulated environment and buoy classification using YOLO for an Autonomous Surface Vessel 

      Øksne, Yrian Hovde; Aanning, Mikal; Odden, Sigurd; Holt, Markus (Bachelor thesis, 2020)
      AutoDrone konkurransen er et nasjonalt maritimt robotikk event holdt av Universitetet i Sør-Øst Norge (USN) og er holdt i Horten, Norge. Konkurransen er åpen for fullstendig autonome og ubenammede båter innen gitte ...
    • Graph-Based Storage In Social Networks 

      Steine, Kristine (Master thesis, 2016)
      How do we efficiently store an ever-growing amount of data? How do we retrieve and analyze relationships between data quickly? These are among the concerns faced by companies such as Google, Yahoo, Amazon, and Facebook ...
    • Graph-theoretic approaches and tools for quantitatively assessing curricula coherence 

      Varagnolo, Damiano; Knorn, Steffi; Staffas, Kjell; Fjällström, Eva; Wrigstad, Tobias (Peer reviewed; Journal article, 2020)
      In this paper, we propose a method to analyse the coherence of existing curricula at higher education institution. We focus our attention to engineering programmes at universities but the proposed method is by no means ...
    • Graphene H-Waveguide for Terahertz Lasing Applications: Electromagnetic Quasi-Linear Theory 

      Kouzaev, Guennadi (Peer reviewed; Journal article, 2020)
      A novel graphene H-waveguide is proposed for active terahertz components. A graphene film illuminated by strong pumping light shorts the parallel conductor plates. The terahertz modes propagating along this film are amplified ...
    • Graphene-Based Transparent Conducting Substrates for GaN/AlGaN Nanocolumn Flip-Chip Ultraviolet Light-Emitting Diodes 

      Liudi Mulyo, Andreas; Mukherjee, Anjan; Høiaas, Ida Marie; Ahtapodov, Lyubomir; Nilsen, Tron Arne; Toftevaag, Håvard Hem; Vullum, Per Erik; Kishino, Katsumi; Weman, Helge; Fimland, Bjørn-Ove (Journal article; Peer reviewed, 2021)
      Flip-chip ultraviolet light-emitting diodes based on self-assembled GaN/AlGaN nanocolumns have been fabricated, exploiting single-layer graphene not only as a growth substrate but also as a transparent conducting electrode. ...