Bilde av Johansen, Thomas Haugland
Bilde av Johansen, Thomas Haugland
Department of Physics and Technology thomas.h.johansen@uit.no +4777625291 +4797078850 Tromsø FPARK B 212

Thomas Haugland Johansen


Head Engineer / Machine Learning


  • Jon Berezowski, Thomas Haugland Johansen, Jonas Nordhaug Myhre, Fred Godtliebsen :
    Variable Depth Bayesian Neural Networks Using Reversible Jumps
    2022 IEEE 32nd International Workshop on Machine Learning for Signal Processing (MLSP) 2022 DOI
  • Sara Maria Björk, Jonas Nordhaug Myhre, Thomas Haugland Johansen :
    Simpler is Better: Spectral Regularization and Up-Sampling Techniques for Variational Autoencoders
    IEEE conference proceedings 2022 DOI
  • Thomas Haugland Johansen, Steffen Aagaard Sørensen, Kajsa Møllersen, Fred Godtliebsen :
    Instance Segmentation of Microscopic Foraminifera
    Applied Sciences 2021 ARKIV / DOI
  • Thomas Haugland Johansen, Steffen Aagaard Sørensen :
    Towards detection and classification of microscopic foraminifera using transfer learning
    Proceedings of the Northern Lights Deep Learning Workshop 2020 ARKIV / DOI
  • Stig Uteng, Thomas Haugland Johansen, Jose Ignacio Zaballos, Samuel Ortega, Lasse Holmström, Gustavo M. Callico et al.:
    Early Detection of Change by Applying Scale-Space Methodology to Hyperspectral Images
    Applied Sciences 2020 ARKIV / DOI
  • Thomas Haugland Johansen, Kajsa Møllersen, Samuel Ortega, Himar Fabelo, Aday Garcia, Gustavo Callico et al.:
    Recent advances in hyperspectral imaging for melanoma detection
    Wiley Interdisciplinary Reviews: Computational Statistics 2019 ARKIV / DOI
  • Thomas Haugland Johansen, Kajsa Møllersen, Samuel Ortega, Himar Fabelo, Gustavo Callico, Fred Godtliebsen :
    Detecting skin cancer using hyperspectral images
    Advanced Science News 2020
  • Thomas Johansen :
    On the improvement and acceleration of eigenvalue decomposition in spectral methods using GPUs
  • Arnt Børre Salberg, Jarle Bauck Hamar, Florina Ardelean, Thomas Johansen, Michael C. Kampffmeyer :
    Automatic detection and segmentation of avalanches in remote sensing images using deep convolutional neural networks
    2016

  • The 50 latest publications is shown on this page. See all publications in Cristin here →



    FPARK B 212

    Click for bigger map