Now showing items 1-3 of 3

    • A Communication Interface for Multilayer Cloud Computing Architecture for Low Cost Underwater Vehicles 

      Cardaillac, Alexandre; Ludvigsen, Martin (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-08-10)
      To enable high computational loads for low cost underwater drones, a cloud based architecture is proposed to take advantage of recent development in machine learning and computer vision. The processing power made available will benefit vehicles with limited onboard processing capacity. The rapid development of cloud computing services have made servers with significant computational resources easier ...
    • Marine Snow Detection for Real Time Feature Detection 

      Cardaillac, Alexandre; Ludvigsen, Martin (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-12-01)
      Underwater images are often degraded due to backscatter, light attenuation and light artifacts. One important aspect of it is marine snow, which are particles of varying shape and size. Computer vision technologies can be strongly affected by them and may therefore provide incorrect and biased results. In robotic applications, there is limited computational power for online processing. A method for ...
    • Semantic Segmentation in Underwater Ship Inspections: Benchmark and Dataset 

      Waszak, Maryna; Cardaillac, Alexandre; Elvesæter, Brian; Rødølen, Frode; Ludvigsen, Martin (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-12-23)
      In this article, we present the first large-scale data set for underwater ship lifecycle inspection, analysis and condition information (LIACI). It contains 1893 images with pixel annotations for ten object categories: defects, corrosion, paint peel, marine growth, sea chest gratings, overboard valves, propeller, anodes, bilge keel and ship hull. The images have been collected during underwater ...