• Automatic autonomous vision-based power line inspection: A review of current status and the potential role of deep learning 

      Nguyen, van Nhan; Jenssen, Robert; Roverso, Davide (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-01-09)
      To maintain the reliability, availability, and sustainability of electricity supply, electricity companies regularly perform visual inspections on their transmission and distribution networks. These inspections have been typically carried out using foot patrol and/or helicopter-assisted methods to plan for necessary repair or replacement works before any major damage, which may cause power outage. ...
    • Intelligent Monitoring and Inspection of Power Line Components Powered by UAVs and Deep Learning 

      Nguyen, van Nhan; Jenssen, Robert; Roverso, Davide (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-01-11)
      In this paper, we present a novel automatic autonomous vision-based power line inspection system that uses unmanned aerial vehicle inspection as the main inspection method, optical images as the primary data source, and deep learning as the backbone of the data analysis. To facilitate the implementation of the system, we address three main challenges of deep learning in vision-based power line ...
    • LS-Net: fast single-shot line-segment detector 

      Nguyen, Van Nhan; Jenssen, Robert; Roverso, Davide (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-10-29)
      In unmanned aerial vehicle (UAV) flights, power lines are considered as one of the most threatening hazards and one of the most difficult obstacles to avoid. In recent years, many vision-based techniques have been proposed to detect power lines to facilitate self-driving UAVs and automatic obstacle avoidance. However, most of the proposed methods are typically based on a common three-step approach: ...