Feature Extraction

Feature Extraction is the process of identifying and transforming raw data into a set of measurable characteristics or attributes that effectively represent the underlying patterns or structures of interest in a given signal, image, or sensory input, distinguishing it from related preprocessing and feature selection techniques by focusing specifically on the derivation of new, reduced-dimension features from原始 data.

19.8K

Publications

1.2M

Citations

48.7K

Authors

6.3K

Institutions

Publications per year

2017–2026

9.1K

Authors

48.7K

  1. DZ
    David Zhang

    Hong Kong Polytechnic University, Hong Kong SAR China

    76 publications · 14.2K citations

    48

    h-index

  2. FN
    Feiping Nie

    Northwestern Polytechnical University, China

    45 publications · 3.4K citations

    31

    h-index

  3. JK
    Jong-Myon Kim

    University of Ulsan, South Korea

    39 publications · 2.1K citations

    28

    h-index

  4. YX
    Yong Xu

    Harbin Institute of Technology, China

    30 publications · 3K citations

    25

    h-index

  5. LZ
    Lei Zhang

    Hong Kong Polytechnic University, Hong Kong SAR China

    34 publications · 3.1K citations

    24

    h-index

1–5 of 48.7K

Venues

  1. Pattern Recognition

    295 publications · 33.9K citations

    85

    h-index

  2. IEEE Access

    558 publications · 26.3K citations

    75

    h-index

  3. IEEE Transactions on Image Processing

    124 publications · 23.8K citations

    71

    h-index

  4. Sensors

    391 publications · 18.4K citations

    69

    h-index

  5. Expert Systems with Applications

    193 publications · 16.7K citations

    67

    h-index

1–5