Pixel-level Feature Engineering

Pixel-Level Feature Engineering is a feature extraction methodology in image processing that operates on individual pixel values as the fundamental unit of analysis, distinguishing itself by deriving or transforming image features directly from raw pixel intensities without relying on higher-level structural or regional abstractions.

35

Publications

1.3K

Citations

135

Authors

58

Institutions

Publications per year

2017–2026

15

Authors

135

  1. CV
    Claus Vielhauer

    Otto-von-Guericke-Universität Magdeburg, Germany

    2 publications · 20 citations

    2

    h-index

  2. JD
    Jana Dittmann

    Otto-von-Guericke-Universität Magdeburg, Germany

    2 publications · 20 citations

    2

    h-index

  3. RM
    Ronny Merkel

    Otto-von-Guericke-Universität Magdeburg, Germany

    2 publications · 20 citations

    2

    h-index

  4. RD
    Robert D. Nowak

    University of Wisconsin–Madison, United States

    1 publications · 15 citations

    1

    h-index

  5. GL
    Guosheng Lin

    Nanyang Technological University, Singapore

    1 publications · 16 citations

    1

    h-index

1–5 of 135

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 31 citations

    2

    h-index

  2. Pattern Recognition

    2 publications · 44 citations

    2

    h-index

  3. Applied Soft Computing

    1 publications · 29 citations

    1

    h-index

  4. Biomedical Signal Processing and Control

    1 publications · 73 citations

    1

    h-index

  5. 1

    h-index

1–5