Artifact Removal

Artifact Removal is a data preprocessing technique that specifically identifies and eliminates spurious or non-representative patterns in datasets arising from measurement errors, technical limitations, or external interferences, thereby preserving the integrity of the underlying phenomena under study.

620

Publications

48.6K

Citations

3.1K

Authors

928

Institutions

Publications per year

2017–2026

278

Authors

3.1K

  1. TJ
    Tzyy‐Ping Jung

    University of California San Diego, United States

    6 publications · 5K citations

    6

    h-index

  2. DM
    Dante Mantini

    KU Leuven, Belgium

    6 publications · 514 citations

    6

    h-index

  3. VR
    Vandana Roy

    Koneru Lakshmaiah Education Foundation, India

    5 publications · 884 citations

    6

    h-index

  4. KS
    Kevin Sweeney

    University College Dublin, Ireland

    5 publications · 824 citations

    5

    h-index

  5. JC
    Jong Chul Ye

    Korea Advanced Institute of Science and Technology, South Korea

    5 publications · 138 citations

    5

    h-index

1–5 of 3.1K

Venues

  1. IEEE Transactions on Biomedical Engineering

    27 publications · 2.2K citations

    22

    h-index

  2. Journal of Neural Engineering

    15 publications · 1.6K citations

    13

    h-index

  3. Sensors

    12 publications · 418 citations

    13

    h-index

  4. Magnetic Resonance in Medicine

    MRM · 11 publications · 2.8K citations

    11

    h-index

  5. Journal of Neuroscience Methods

    11 publications · 985 citations

    11

    h-index

1–5