Browsing NTNU Open by Author "Stahl, Annette"

Now showing items 61-80 of 105

    • MOG: a background extraction approach for data augmentation of time-series images in deep learning segmentation 

      Borgersen, Jonas Nagell; Saad, Aya; Stahl, Annette (Journal article; Peer reviewed, 2021)
      Image segmentation is one of the key components in systems performing computer vision recognition tasks. Various algorithms for image segmentation have been developed in the literature. Among them, more recently, deep ...

    • Monitoring Algal Blooms with Complementary Sensors on Multiple Spatial and Temporal Scales 

      Williamson, David Roddan; Moreira Fragoso, Glaucia; Majaneva, Sanna Kristiina; Dallolio, Alberto; Halvorsen, Daniel Ørnes; Hasler, Oliver Kevin; Oudijk, Adriënne Esmeralda; Langer, Dennis David; Johansen, Tor Arne; Johnsen, Geir; Stahl, Annette; Ludvigsen, Martin; Garrett, Joseph Landon (Peer reviewed; Journal article, 2023)

    • Motion Trajectory Estimation of Salmon Using Stereo Vision 

      Nygård, Trym Anthonsen; Jahren, Jan Henrik; Schellewald, Christian; Stahl, Annette (Peer reviewed; Journal article, 2022)
      A main concern for the aquaculture industry is the fish behaviour and welfare. Motion trajectory analysis of salmon at aquaculture farming sites with respect to certain aquaculture operations aims to provide information ...

    • Multi-Sensor Tracking for Autonomous Surface Vehicles 

      Helgesen, Øystein Kaarstad (Doctoral theses at NTNU;2023:84, Doctoral thesis, 2023)
      Maritime autonomy is rapidly gaining interest both in academic and industrial circles. Safe navigation for autonomous surface vehicles requires a robust and reliable tracking system that maintains and estimates the positions ...

    • Multimodal Multispectral Imaging System for Small UAVs 

      Haavardsholm, Trym Vegard; Skauli, Torbjørn; Stahl, Annette (Peer reviewed; Journal article, 2020)
      Multispectral imaging is an attractive sensing modality for small unmanned aerial vehicles (UAVs) in numerous applications. The most compact spectral camera architecture is based on spectral filters in the focal plane. ...

    • Mutual Information Maximization by Data Augmentation for Plankton Classification 

      Kwizera, Fred (Master thesis, 2023)
      Denne masteroppgaven utforsker potensialet for ikke-veiledet maskinlæring for in-situ plankton bildeklassifisering. Oppgaven ble utformet for å adressere begrensningene i bildeklassifisering ved veiledet maskinlæring, ...

    • Object detection and instance segmentation of planktonic organisms using Mask R-CNN for real-time in-situ image processing. 

      Bergum, Sondre A. (Master thesis, 2020)
      Denne oppgaven er en undersøkelse av nylig presenterte state-of-the-art metoder og nettverksarkitekturer for bildesegmentering[61, 38, 37, 78, 49] ved bruk av Facebook Artificial Intelligence Research (FAIR) sitt software ...

    • Optical flow applied to infant movement 

      Kirkerød, Harald (Master thesis, 2010)
      Healthy infants in the age group of 9 to 20 weeks post term have a distinct movement pattern called fidgety movements. The abscense of, or anomalies in these movements are indications that the infant may suffer from Cerebral ...

    • Optimization of Mask R-CNN algorithm for corrosion detection using Genetic Algorithm and sky segmentation 

      Semb, Helene (Master thesis, 2023)
      Denne oppgaven tar sikte på å studere og vurdere strategier for å forbedre et nevralt nettverk for å oppdage og segmentere korrosjonsskader fra broinspeksjoner. For å evaluere effekten av bildene, ble datasettet innsnevret ...

    • Passive depth estimation using stereo vision, an experimental study 

      Høklie, Jørgen Jøsok (Master thesis, 2017)
      This master s thesis is an experimental study on passive stereo techniques for retrieving 3D scene information. The stereo camera system is tested for finding the position of a platform relative to the stereo camera where ...

    • Positioning a camera underwater 

      Mathisen, Henriette Sommerseth (Master thesis, 2022)
      Denne masteroppgaven gir en oversikt over hvordan utfordringene med posisjonering og orientering under vann var undersøkt, ved å benytte et billig og enkelt system. Utfordringene med å posisjonere og orientere et kamera ...

    • Post-processing and visualization techniques for isogeometric analysis results 

      Stahl, Annette; Kvamsdal, Trond; Schellewald, Christian (Journal article; Peer reviewed, 2016)
      Isogeometric Analysis (IGA) introduced in 2005 by Hughes et al. (2005) [1] exploits one mathematical basis representation for computer aided design (CAD), geometry and analysis during the entire engineering process. In ...

    • Precision fish farming: A new framework to improve production in aquaculture 

      Føre, Martin; Frank, Kevin; Norton, Tomas; Svendsen, Eirik; Alfredsen, Jo Arve; Dempster, Timothy David; Eguiraun, Harkaitz; Watson, Win; Stahl, Annette; Sunde, Leif Magne; Schellewald, Christian; Skøien, Kristoffer Rist; Alver, Morten; Berckmans, Daniel (Journal article; Peer reviewed, 2017)
      Aquaculture production of finfish has seen rapid growth in production volume and economic yield over the last decades, and is today a key provider of seafood. As the scale of production increases, so does the likelihood ...

    • Progressive integration of visibility constraints for implicit functions 

      Haugo, Simen; Stahl, Annette (Peer reviewed; Journal article, 2022)
      Procedurally-defined implicit functions, such as CSG trees and recent neural shape representations, offer compelling benefits for modeling scenes and objects, including infinite resolution, differentiability and trivial ...

    • Real-time Corrections for a Low-cost Hyperspectral Instrument 

      Henriksen, Marie Bøe; Garrett, Joseph; Prentice, Elizabeth Frances; Sigernes, Fred; Stahl, Annette; Johansen, Tor Arne (Journal article; Peer reviewed, 2019)
      The development of a hyperspectral imager (HSI) made from commercial off-the-shelf (COTS) parts enables the use of hyperspectral imaging on smaller low-cost platforms such as cubesats, drones, or other autonomous vehicles. ...

    • Real-time Depth Estimation System for Autonomous Racing 

      Elzoghby, Waleed (Master thesis, 2020)
      Dette prosjektet hadde til hensikt å bygge et system for visuell persepsjon som skal brukes av Revolves autonome racerbil "ATMOS" i mål om å vinne de internasjonale Formula Student Driverless-konkurransene der bilen vil ...

    • Robot learning with visual processing in arbitrarily sized, high resolution volumes 

      Dyrstad, Jonatan Sjølund (Doctoral theses at NTNU;2023:266, Doctoral thesis, 2023)
      Flexible robots, capable of manipulating objects in unstructured environments under changing conditions, will lead to a paradigm shift in automation. Such robotic solutions can potentially transform entire industries ...

    • Robust Deep Unsupervised Learning Framework to Discover Unseen Plankton Species 

      Salvesen, Eivind; Saad, Aya; Stahl, Annette (Journal article; Peer reviewed, 2021)
      Deep convolutional neural networks have proven effective in computer vision, especially in the task of image classification. Nevertheless, the success is limited to supervised learning approaches, requiring extensive amounts ...

    • Robust Fish Cage Hole Detection in Challenging Environments - Rethinking Spatiotemporal Deep Learning and Advanced Computer Vision Techniques 

      Madshaven, Arild (Master thesis, 2021)
      I 2019 alene ble nesten 300.000 atlanterhavslaks rapportert rømt fra norske oppdrettsanlegg. Dette antallet tilsvarer over halve den gjenværende villaksbestanden. En vanlig fluktrute går gjennom hull i nota, og regelmessig ...

    • Robust Volumetric 3-D Reconstruction in a Dynamic Environment 

      Angelsen, Roy Konrad (Master thesis, 2018)
      As a part of a research project at SINTEF Ocean AS named Neodroid aiming at developing a general purpose humanoid robot to execute a variety of complex tasks, the need for perceptive ability arises. The robot consists of ...