Semi-supervised Scene Classification

Semi-Supervised Scene Classification is a scene classification paradigm that integrates a small set of labeled scene images with a large collection of unlabeled scene images to improve classification accuracy by leveraging both supervised and unsupervised learning mechanisms.

30

Publications

1.4K

Citations

122

Authors

62

Institutions

Publications per year

2017–2026

27

Authors

122

  1. JM
    Jie Mei

    Beijing Normal University, China

    2 publications · 22 citations

    2

    h-index

  2. YW
    Yuebin Wang

    Beijing Normal University, China

    2 publications · 22 citations

    2

    h-index

  3. LZ
    Liqiang Zhang

    Beijing Normal University, China

    2 publications · 22 citations

    2

    h-index

  4. TR
    Tom Rune Lauknes

    Northern Research Institute, Norway

    1 publications · 38 citations

    1

    h-index

  5. HH
    Haiyang Huang

    Beijing Normal University, China

    1 publications · 12 citations

    1

    h-index

1–5 of 122

Venues

  1. 4

    h-index

  2. Remote Sensing

    2 publications · 53 citations

    2

    h-index

  3. IEEE Access

    2 publications · 59 citations

    2

    h-index

  4. Information Fusion

    2 publications · 94 citations

    2

    h-index

  5. Neurocomputing

    2 publications · 76 citations

    2

    h-index

1–5