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Drivers stress identification in real-world driving tasks

Abstract
Data di Pubblicazione:
2022
Abstract:
In the past few years, cross-modal distillation has garnered a lot of interest due to the rapid growth of multi-modal data. In this paper, we study stress recognition of the drivers corresponding to the driving situation. Our method enables us to recognize stress from unlabeled videos. We perform cross-modal distillation based on wearable physiological sensors and videos from on-board cameras. In this cross-modal distillation, knowledge is transferred from sensor to vision modality.
Tipologia CRIS:
04.02 Abstract in Atti di convegno
Keywords:
Cross-modal transfer; Deep Learning; Stress detection
Elenco autori:
Bano, Saira; Gotta, Alberto
Autori di Ateneo:
GOTTA ALBERTO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/417673
Link al Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/417673/100689/prod_471816-doc_191771.pdf
Titolo del libro:
2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)
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URL

https://ieeexplore.ieee.org/document/9767455
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