Multi-scale Feature Detection

Multi-Scale Feature Detection is a computational method in computer vision that identifies image features across multiple spatial scales to enhance robustness to variations in size, resolution, and distance by systematically analyzing structures at differing levels of detail.

698

Publications

46.6K

Citations

2.4K

Authors

621

Institutions

Publications per year

2017–2026

577

Authors

2.4K

  1. LJ
    Licheng Jiao

    Xidian University, China

    4 publications · 225 citations

    4

    h-index

  2. WJ
    Weikuan Jia

    Shandong Normal University, China

    4 publications · 66 citations

    4

    h-index

  3. KF
    Kun Fu

    Chinese Academy of Sciences, China

    3 publications · 883 citations

    3

    h-index

  4. YY
    Yang Yang

    Yunnan Normal University, China

    3 publications · 262 citations

    3

    h-index

  5. FS
    Fahad Shahbaz Khan

    Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates

    3 publications · 129 citations

    3

    h-index

1–5 of 2.4K

Venues

  1. Remote Sensing

    28 publications · 2K citations

    24

    h-index

  2. IEEE Access

    36 publications · 1.7K citations

    24

    h-index

  3. Sensors

    22 publications · 1.1K citations

    19

    h-index

  4. 15

    h-index

  5. Pattern Recognition

    12 publications · 779 citations

    13

    h-index

1–5