Image-based Defect Assessment

Image-Based Defect Assessment is a methodological framework within asset condition assessment that uses visual data captured through imaging technologies to identify, classify, and quantify defects in engineered systems or structures, distinguishing itself by relying on image analysis algorithms and computer vision techniques rather than physical sensors or manual inspection.

180

Publications

6.6K

Citations

688

Authors

238

Institutions

Publications per year

2017–2026

94

Authors

688

  1. MD
    Matthias Demant

    Fraunhofer Institute for Solar Energy Systems, Germany

    3 publications · 58 citations

    3

    h-index

  2. RO
    Ronnie O. Serfa Juan

    Kyungpook National University, South Korea

    3 publications · 63 citations

    3

    h-index

  3. SR
    Stefan Rein

    Fraunhofer Institute for Solar Energy Systems, Germany

    3 publications · 58 citations

    3

    h-index

  4. IB
    Ioannis Brilakis

    University of Cambridge, United Kingdom

    2 publications · 112 citations

    2

    h-index

  5. SL
    Sangwook Lee

    University of Ulsan, South Korea

    2 publications · 58 citations

    2

    h-index

1–5 of 688

Venues

  1. NDT & E International

    11 publications · 691 citations

    11

    h-index

  2. 5

    h-index

  3. 4

    h-index

  4. 4

    h-index

  5. Applied Sciences

    4 publications · 173 citations

    4

    h-index

1–5