Feature Quantization

Feature Quantization is a method in image feature engineering that discretizes continuous feature representations into a finite set of discrete values or bins to reduce dimensionality and enhance computational efficiency while preserving discriminative information.

414

Publications

32.2K

Citations

1.2K

Authors

455

Institutions

Publications per year

2017–2026

159

Authors

1.2K

  1. TV
    Thomas Villmann

    Hochschule Mittweida, Germany

    13 publications · 769 citations

    11

    h-index

  2. BH
    Barbara Hammer

    Bielefeld University, Germany

    10 publications · 909 citations

    10

    h-index

  3. MB
    Michael Biehl

    University of Groningen, Netherlands

    9 publications · 517 citations

    9

    h-index

  4. PS
    Petra Schneider

    ETH Zurich, Switzerland

    5 publications · 456 citations

    5

    h-index

  5. FS
    Frank-Michael Schleif

    Leipzig University, Germany

    5 publications · 102 citations

    5

    h-index

1–5 of 1.2K

Venues

  1. arXiv (Cornell University)

    Repository · 27 publications · 2.6K citations

    18

    h-index

  2. Neurocomputing

    21 publications · 646 citations

    17

    h-index

  3. IEEE Transactions on Image Processing

    16 publications · 1.1K citations

    13

    h-index

  4. 9

    h-index

  5. Pattern Recognition Letters

    9 publications · 354 citations

    9

    h-index

1–5