• Applying Object Detection to Marine Data and Exploring Explainability of a Fully Convolutional Neural Network Using Principal Component Analysis 

      Stavelin, Peter Herman; Rasheed, Adil; San, Omer; Hestnes, Arne Johan (Peer reviewed; Journal article, 2021)
      With the rise of focus on man made changes to our planet and wildlife therein, more and more emphasis is put on sustainable and responsible gathering of resources. In an effort to preserve maritime wildlife the Norwegian ...
    • Order theory for discrete gradient methods 

      Eidnes, Sølve (Peer reviewed; Journal article, 2022)
      The discrete gradient methods are integrators designed to preserve invariants of ordinary differential equations. From a formal series expansion of a subclass of these methods, we derive conditions for arbitrarily high ...
    • Robot-supervised Learning of Crop Row Segmentation 

      Bakken, Marianne; Ponnambalam, Vignesh Raja; Moore, Richard J.D.; Omholt Gjevestad, Jon Glenn; From, Pål Johan (Chapter; Peer reviewed, 2021)
      We propose an approach for robot-supervised learning that automates label generation for semantic segmentation with Convolutional Neural Networks (CNNs) for crop row detection in a field. Using a training robot equipped ...