Unsupervised Defect Classification

Unsupervised Defect Classification is a defect classification approach that autonomously identifies and categorizes defects without relying on labeled training data by leveraging intrinsic data structures and patterns.

25

Publications

1.5K

Citations

97

Authors

43

Institutions

Publications per year

2017–2026

14

Authors

97

  1. TB
    Teguh Bharata Adji

    Universitas Gadjah Mada, Indonesia

    2 publications · 30 citations

    2

    h-index

  2. RF
    Ridi Ferdiana

    Universitas Gadjah Mada, Indonesia

    2 publications · 30 citations

    2

    h-index

  3. AM
    Aris Marjuni

    Universitas Gadjah Mada, Indonesia

    2 publications · 30 citations

    2

    h-index

  4. BM
    B.G. Mertzios

    Democritus University of Thrace, Greece

    1 publications · 20 citations

    1

    h-index

  5. HF
    Hiromitsu Fujii

    The University of Tokyo, Japan

    1 publications · 12 citations

    1

    h-index

1–5 of 97

Venues

  1. Sensors

    3 publications · 51 citations

    3

    h-index

  2. IEEE Access

    2 publications · 64 citations

    2

    h-index

  3. 1

    h-index

  4. Journal of Manufacturing Processes

    JMP · 1 publications · 66 citations

    1

    h-index

  5. Journal Of Big Data

    1 publications · 18 citations

    1

    h-index

1–5