Cargando…
A Generic Design of Driver Drowsiness and Stress Recognition Using MOGA Optimized Deep MKL-SVM
Driver drowsiness and stress are major causes of traffic deaths and injuries, which ultimately wreak havoc on world economic loss. Researchers are in full swing to develop various algorithms for both drowsiness and stress recognition. In contrast to existing works, this paper proposes a generic mode...
Autores principales: | Chui, Kwok Tai, Lytras, Miltiadis D., Liu, Ryan Wen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085776/ https://www.ncbi.nlm.nih.gov/pubmed/32156100 http://dx.doi.org/10.3390/s20051474 |
Ejemplares similares
-
Research on lung nodule recognition algorithm based on deep feature fusion and MKL-SVM-IPSO
por: Li, Yang, et al.
Publicado: (2022) -
Extended-Range Prediction Model Using NSGA-III Optimized RNN-GRU-LSTM for Driver Stress and Drowsiness
por: Chui, Kwok Tai, et al.
Publicado: (2021) -
Moving Towards Intelligent Transportation via Artificial Intelligence and Internet-of-Things
por: Lytras, Miltiadis D., et al.
Publicado: (2020) -
Research on Key Algorithms of the Lung CAD System Based on Cascade Feature and Hybrid Swarm Intelligence Optimization for MKL-SVM
por: Chang, Jiayue, et al.
Publicado: (2021) -
Fusion of Optimized Indicators from Advanced Driver Assistance Systems (ADAS) for Driver Drowsiness Detection
por: Daza, Iván G., et al.
Publicado: (2014)