Robust Emotion Recognition

Robust Emotion Recognition is an emotion recognition framework that maintains high accuracy and reliability across diverse, noisy, and variable real-world conditions, such as differing modalities, cultural contexts, individual differences, and environmental disturbances, thereby distinguishing itself from conventional emotion recognition systems through its resilience to perturbations and generalizability beyond controlled settings.

149

Publications

8.5K

Citations

486

Authors

215

Institutions

Publications per year

2017–2026

94

Authors

486

  1. BW
    Björn W. Schuller

    Imperial College London, United Kingdom

    11 publications · 867 citations

    11

    h-index

  2. CB
    Carlos Busso

    The University of Texas at Dallas, United States

    5 publications · 255 citations

    5

    h-index

  3. GR
    Gerhard Rigoll

    Technical University of Munich, Germany

    5 publications · 615 citations

    5

    h-index

  4. BV
    Bogdan Vlasenko

    Otto-von-Guericke-Universität Magdeburg, Germany

    4 publications · 168 citations

    4

    h-index

  5. CL
    Chi-Chun Lee

    National Tsing Hua University, Taiwan

    4 publications · 117 citations

    4

    h-index

1–5 of 486

Venues

  1. IEEE Transactions on Affective Computing

    TAC · 9 publications · 665 citations

    9

    h-index

  2. IEEE Access

    8 publications · 633 citations

    8

    h-index

  3. Sensors

    5 publications · 223 citations

    5

    h-index

  4. arXiv (Cornell University)

    Repository · 5 publications · 133 citations

    5

    h-index

  5. Multimedia Tools and Applications

    3 publications · 74 citations

    3

    h-index

1–5