• Multi-sensor and time-series approaches for monitoring of snow parameters 

  Solberg, Rune; Amlien, Jostein; Koren, Hans; Eikvil, Line; Malnes, Eirik; Storvold, Rune (Chapter, 2004)

  Frequent mapping of snow parameters, like snow cover area (SCA) and snow surface wetness (SSW), is important for applications in hydrology, meteorology and climatology. In this study, we have developed a few general ...

• Adaptive registration of remote sensing images using supervised learning 

  Eikvil, Line; Holden, Marit; Huseby, Ragnar Bang (Peer reviewed; Journal article, 2009)

  This paper describes a system for co-registration of time series satellite images which uses a learning-based strategy. During a training phase, the system learns to recognize regions in an image suited for registration. ...

• Method development for mapping kelp using drones and satellite images: Results from the KELPMAP-Vega project 

  Gundersen, Hege; Hancke, Kasper; Salberg, Arnt Børre; Poulsen, Robert Nøddebo; Buls, Toms; Liu, Izzie Yi; Ghareeb, Medyan; Christie, Hartvig C; Kile, Maia Røst; Bekkby, Trine; Arvidsson, Karoline Slettebø; Kvile, Kristina Øie (NIVA-rapport;, Research report, 2024)

  The KELPMAP study demonstrated that high-resolution multispectral data from drones and satellites, combined with AI-based image analysis, can efficiently map kelp forests and other coastal habitats. The field campaign, ...

• IoT cybersecurity in 5G and beyond: a systematic literature review 

  Pirbhulal, Sandeep; Chockalingam, Sabarathinam; Shukla, Ankur; Abie, Habtamu (Journal article; Peer reviewed, 2024)

  The 5th generation (5G) and beyond use Internet of Things (IoT) to offer the feature of remote monitoring for different applications such as transportation, healthcare, and energy. There are several advantages of 5G and ...

• Leveraging tensor kernels to reduce objective function mismatch in deep clustering 

  Trosten, Daniel Johansen; Løkse, Sigurd Eivindson; Jenssen, Robert; Kampffmeyer, Michael Christian (Journal article; Peer reviewed, 2024)

  Objective Function Mismatch (OFM) occurs when the optimization of one objective has a negative impact on the optimization of another objective. In this work we study OFM in deep clustering, and find that the popular ...

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