Aggregating CNN and HOG features for Real-Time Distracted Driver Detection
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/8656627/8661828/08661970.pdf?arnumber=8661970
Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. CBAM VGG16: An efficient driver distraction classification using CBAM embedded VGG16 architecture;Computers in Biology and Medicine;2024-09
2. Multi-Modal Deep Learning Architecture for Accurate Driver Behavior Recognition in Automated Driving Systems;2023 18th International Conference on Intelligent Systems and Knowledge Engineering (ISKE);2023-11-17
3. CAT-CapsNet: A Convolutional and Attention Based Capsule Network to Detect the Driver’s Distraction;IEEE Transactions on Intelligent Transportation Systems;2023-09
4. FRNet: DCNN for Real-Time Distracted Driving Detection Toward Embedded Deployment;IEEE Transactions on Intelligent Transportation Systems;2023-09
5. Swin-Fusion: Swin-Transformer with Feature Fusion for Human Action Recognition;Neural Processing Letters;2023-07-20
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