Image-based Defect Classification

Image-Based Defect Classification is a methodological framework within defect classification that utilizes visual data representations as primary inputs to identify, categorize, and localize anomalies or faults in materials, products, or systems through computational image analysis techniques.

683

Publications

32.7K

Citations

2.4K

Authors

748

Institutions

Publications per year

2017–2026

453

Authors

2.4K

  1. HN
    Hongjun Ni

    Nantong University, China

    4 publications · 184 citations

    4

    h-index

  2. JZ
    Juan Zapata

    Universidad Politécnica de Cartagena, Spain

    4 publications · 331 citations

    4

    h-index

  3. HJ
    Hongquan Jiang

    Xi'an Jiaotong University, China

    4 publications · 180 citations

    4

    h-index

  4. LC
    Luh‐Maan Chang

    National Taiwan University, Taiwan

    4 publications · 277 citations

    4

    h-index

  5. KX
    Ke Xu

    University of Science and Technology Beijing, China

    4 publications · 259 citations

    4

    h-index

1–5 of 2.4K

Venues

  1. IEEE Access

    18 publications · 683 citations

    17

    h-index

  2. Applied Sciences

    18 publications · 846 citations

    16

    h-index

  3. NDT & E International

    18 publications · 1.1K citations

    15

    h-index

  4. Expert Systems with Applications

    14 publications · 927 citations

    14

    h-index

  5. Journal of Intelligent Manufacturing

    14 publications · 663 citations

    14

    h-index

1–5