A Deep Learning Model Based On Multi-granularity Facial Features And LSTM Network For Driver Drowsiness Detection

A Deep Learning Model Based On Multi-granularity Facial Features And LSTM Network For Driver Drowsiness Detection

Driver drowsiness can cause serious harm to drivers and other road participants. Exploring objective and efficient methods for detecting driver drowsiness has important application value for ensuring road safety. Considering the information complementary between local and global facial features for...

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Bibliographic Details
Main Authors: Taiguo Li, Chao Li
Format: Article
Language:English
Published: Tamkang University Press 2024-07-01
Series:Journal of Applied Science and Engineering
Subjects:
driver drowsiness detection
deep learning model
multi-granularity representation features
vision transformer
long short term memory network
Online Access:http://jase.tku.edu.tw/articles/jase-202407-27-7-0011

Internet

http://jase.tku.edu.tw/articles/jase-202407-27-7-0011

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