Automated Affective Computing Based on Bio-Signals Analysis and Deep Learning Approach
- DOI
- 10.3390/s22051789
- Published
- 2022-02-24
- Container
- Sensors
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/s22051789,
title = {Automated Affective Computing Based on Bio-Signals Analysis and Deep Learning Approach},
author = {Chiara Filippini and Adolfo Di Crosta and Rocco Palumbo and David Perpetuini and Daniela Cardone and Irene Ceccato and Alberto Di Domenico and Arcangelo Merla},
year = {2022},
journal = {Sensors},
doi = {10.3390/s22051789},
url = {https://doi.org/10.3390/s22051789}
}RIS
TY - JOUR TI - Automated Affective Computing Based on Bio-Signals Analysis and Deep Learning Approach AU - Chiara Filippini AU - Adolfo Di Crosta AU - Rocco Palumbo AU - David Perpetuini AU - Daniela Cardone AU - Irene Ceccato AU - Alberto Di Domenico AU - Arcangelo Merla PY - 2022 JO - Sensors DO - 10.3390/s22051789 UR - https://doi.org/10.3390/s22051789 ER -
APA
Filippini, C., Crosta, A. D., Palumbo, R., Perpetuini, D., Cardone, D., Ceccato, I., Domenico, A. D., & Merla, A. (2022). Automated Affective Computing Based on Bio-Signals Analysis and Deep Learning Approach. Sensors. https://doi.org/10.3390/s22051789
Source records
- crossref · retrieved 2026-09-24T20:07:12.469Z