Scale-invariant Feature Transform

Scale-Invariant Feature Transform is a feature detection and description algorithm in computer vision that identifies distinctive, scale-stable keypoints and their associated descriptors in an image, enabling robust matching across varying scales, rotations, and affine transformations.

1.5K

Publications

127.8K

Citations

4.8K

Authors

1.4K

Institutions

Publications per year

2017–2026

500

Authors

4.8K

  1. PK
    Patrik Kamencay

    University of Žilina, Slovakia

    7 publications · 221 citations

    7

    h-index

  2. MR
    Marco Riboldi

    Politecnico di Milano, Italy

    6 publications · 216 citations

    6

    h-index

  3. UC
    Umesh Chandra Pati

    National Institute of Technology Rourkela, India

    6 publications · 199 citations

    6

    h-index

  4. GB
    G. Baroni

    Politecnico di Milano, Italy

    6 publications · 216 citations

    6

    h-index

  5. XL
    Xuelong Li

    Xi'an Institute of Optics and Precision Mechanics, China

    6 publications · 431 citations

    6

    h-index

1–5 of 4.8K

Venues

  1. IEEE Geoscience and Remote Sensing Letters

    GRSL · 43 publications · 3.8K citations

    32

    h-index

  2. IEEE Transactions on Image Processing

    42 publications · 3.4K citations

    29

    h-index

  3. 22

    h-index

  4. Remote Sensing

    30 publications · 1.3K citations

    20

    h-index

  5. Sensors

    25 publications · 761 citations

    19

    h-index

1–5