Now showing items 1-2 of 2

    • Eddy Detection in the Marginal Ice Zone with Sentinel-1 Data Using YOLOv5 

      Khachatrian, Eduard; Sandalyuk, Nikita V.; Lozou, Pigi (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-04-24)
      The automatic detection and analysis of ocean eddies in the marginal ice zone via remote sensing is a very challenging task but of critical importance for scientific applications and anthropogenic activities. Therefore, as one of the first steps toward the automation of the eddy detection process, we investigated the potential of applying YOLOv5, a deep convolutional neural network architecture, to ...
    • On Measures of Uncertainty in Classification 

      Chlaily, Saloua; Ratha, Debanshu; Lozou, Pigi; Marinoni, Andrea (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-10-12)
      Uncertainty is unavoidable in classification tasks and might originate from data (e.g., due to noise or wrong labeling), or the model (e.g., due to erroneous assumptions, etc). Providing an assessment of uncertainty associated with each outcome is of paramount importance in assessing the reliability of classification algorithms, especially on unseen data. In this work, we propose two measures of ...