Application of a parametric supermatrix multi-task multimodal deep learning model based on electroencephalogram and peripheral physiological signal fusion in emotion recognition.
- DOI
- 10.3389/fnins.2026.1894285
- Published
- 2026
- Container
- Frontiers in neuroscience
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3389/fnins.2026.1894285,
title = {Application of a parametric supermatrix multi-task multimodal deep learning model based on electroencephalogram and peripheral physiological signal fusion in emotion recognition.},
author = {Li X and Gong P and Li C and Ding X and Chen F},
year = {2026},
journal = {Frontiers in neuroscience},
doi = {10.3389/fnins.2026.1894285},
url = {https://doi.org/10.3389/fnins.2026.1894285}
}RIS
TY - JOUR TI - Application of a parametric supermatrix multi-task multimodal deep learning model based on electroencephalogram and peripheral physiological signal fusion in emotion recognition. AU - Li X AU - Gong P AU - Li C AU - Ding X AU - Chen F PY - 2026 JO - Frontiers in neuroscience DO - 10.3389/fnins.2026.1894285 UR - https://doi.org/10.3389/fnins.2026.1894285 ER -
APA
X, L., P, G., C, L., X, D., & F, C. (2026). Application of a parametric supermatrix multi-task multimodal deep learning model based on electroencephalogram and peripheral physiological signal fusion in emotion recognition.. Frontiers in neuroscience. https://doi.org/10.3389/fnins.2026.1894285
Source records
- pubmed · retrieved 2026-09-26T07:10:26.278Z