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This paper is in the following e-collection/theme issue:

Artificial Intelligence (2347) Applications of AI (344) Clinical Informatics (1444) Imaging Informatics (331) Machine Learning (2229)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/68942, first published .
Facial Emotion Recognition of 16 Distinct Emotions From Smartphone Videos: Comparative Study of Machine Learning and Human Performance

Facial Emotion Recognition of 16 Distinct Emotions From Smartphone Videos: Comparative Study of Machine Learning and Human Performance

Facial Emotion Recognition of 16 Distinct Emotions From Smartphone Videos: Comparative Study of Machine Learning and Human Performance

Authors of this article:

Marie Keinert1 Author Orcid Image ;   Simon Pistrosch2, 3 Author Orcid Image ;   Adria Mallol-Ragolta2, 3 Author Orcid Image ;   Björn W Schuller2, 3, 4, 5 Author Orcid Image ;   Matthias Berking1 Author Orcid Image
Article Authors Cited by (4) Tweetations (2) Metrics

Journals

  1. Hatipoglu Yilmaz B, Yilmaz C, Kose C. EEG-based fusion approaches in multimodal emotion recognition: An in-depth review. Neurocomputing 2026;666:132235 View
  2. He J. Interactive graph emotion recognition based on multi-modal data enhancement. Scientific Reports 2026;16(1) View
  3. Xiang G, Xia J, Wei X, Liang Y, Lin Y, Luo R, Li G, Sui M, Jiang N, Liu Z. Functional Assessment of Hemifacial Spasm Using a Whole-Face Surface Electromyography Electrode Array. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2026;34:1528 View

Conference Proceedings

  1. Babu E, Rao B, Manoj S, Pranathi S, Sai S, Prashanth R. 2025 International Conference on Intelligent Computing, Information and Control Systems (ICOIICS). Stress Classification using Deep Learning and AI-Driven Music Therapy View