Gabor Filter Models

Gabor Filter Models is a computational neuroscience framework that uses Gabor functions to simulate cortical receptive fields for modeling spatial contrast sensitivity in early visual processing.

1K

Publications

57.9K

Citations

2.7K

Authors

995

Institutions

Publications per year

2017–2026

222

Authors

2.7K

  1. RM
    Rangaraj M. Rangayyan

    University of Calgary, Canada

    13 publications · 600 citations

    12

    h-index

  2. DZ
    David Zhang

    Hong Kong Polytechnic University, Hong Kong SAR China

    11 publications · 2.5K citations

    11

    h-index

  3. OC
    Ole Christensen

    Technical University of Denmark, Denmark

    9 publications · 498 citations

    9

    h-index

  4. AC
    Alan C. Bovik

    The University of Texas at Austin, United States

    8 publications · 454 citations

    8

    h-index

  5. JB
    Josef Bigün

    Halmstad University, Sweden

    8 publications · 227 citations

    8

    h-index

1–5 of 2.7K

Venues

  1. Pattern Recognition

    24 publications · 3.4K citations

    22

    h-index

  2. Journal of Fourier Analysis and Applications

    23 publications · 1.2K citations

    19

    h-index

  3. Pattern Recognition Letters

    26 publications · 1.7K citations

    18

    h-index

  4. Applied and Computational Harmonic Analysis

    20 publications · 822 citations

    17

    h-index

  5. IEEE Transactions on Image Processing

    17 publications · 3.2K citations

    16

    h-index

1–5