Neural Network Classification

Neural Network Classification is a machine learning approach that employs interconnected layers of artificial neurons to model complex, non-linear relationships in data for the purpose of assigning input samples to predefined categories based on learned patterns.

7K

Publications

476.5K

Citations

20.2K

Authors

4.6K

Institutions

Publications per year

2017–2026

2.5K

Authors

20.2K

  1. RS
    Rudy Setiono

    National University of Singapore, Singapore

    14 publications · 2.2K citations

    14

    h-index

  2. GA
    Gail A. Carpenter

    Boston University, United States

    13 publications · 9.5K citations

    13

    h-index

  3. SO
    Sung‐Kwun Oh

    University of Alberta, Canada

    15 publications · 493 citations

    13

    h-index

  4. WP
    Witold Pedrycz

    University of Alberta, Canada

    12 publications · 383 citations

    12

    h-index

  5. RP
    Richard P. Lippmann

    MIT Lincoln Laboratory, United States

    12 publications · 9.7K citations

    12

    h-index

1–5 of 20.2K

Venues

  1. IEEE Transactions on Neural Networks

    197 publications · 29.4K citations

    84

    h-index

  2. arXiv (Cornell University)

    Repository · 143 publications · 11.6K citations

    43

    h-index

  3. IEEE Access

    105 publications · 5.9K citations

    39

    h-index

  4. Neurocomputing

    79 publications · 8.9K citations

    38

    h-index

  5. Neural Networks

    64 publications · 10.8K citations

    37

    h-index

1–5