Semantically-Enhanced Feature Extraction with CLIP and Transformer Networks for Driver Fatigue Detection

Semantically-Enhanced Feature Extraction with CLIP and Transformer Networks for Driver Fatigue Detection

Drowsy driving is a leading cause of commercial vehicle traffic crashes. The trend is to train fatigue detection models using deep neural networks on driver video data, but challenges remain in coarse and incomplete high-level feature extraction and network architecture optimization. This paper pion...

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Bibliographic Details
Main Authors: Zhen Gao, Xiaowen Chen, Jingning Xu, Rongjie Yu, Heng Zhang, Jinqiu Yang
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Sensors
Subjects:
fatigue detection
CLIP pre-trained model
Transformer
instance normalization
semantic analysis
Online Access:https://www.mdpi.com/1424-8220/24/24/7948
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