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A Real-time Fatigue Detection System using Multi-Task Casca..:
, In:
2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT)
,
P, Raja Mohana S
;
S, Manu Vidhya
;
D, Reshma
- p. 674-679 , 2021
Link:
https://doi.org/10.1109/CSNT51715.2021.9509627
RT T1 <cTitle>2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT)</cTitle>: T1 <Title>A Real-time Fatigue Detection System using Multi-Task Cascaded CNN Model</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9509627&Exemplar=1&LAN=DE A1 P, Raja Mohana S A1 S, Manu Vidhya A1 D, Reshma YR 2021 K1 Support vector machines K1 Computer architecture K1 Fatigue K1 Feature extraction K1 Robustness K1 Convolutional neural networks K1 Automobiles K1 Driver Fatigue K1 Deep-learning K1 Convolutional Neural Network K1 Support Vector Machine K1 Video sequences K1 Haar Cascade SP 674 OP 679 LK http://dx.doi.org/https://doi.org/10.1109/CSNT51715.2021.9509627 DO https://doi.org/10.1109/CSNT51715.2021.9509627 SF ELIB - SuUB Bremen
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