FPT: Fine-Grained Detection of Driver Distraction Based on the Feature Pyramid Vision Transformer-Reference-Cited by-同舟云学术

FPT: Fine-Grained Detection of Driver Distraction Based on the Feature Pyramid Vision Transformer

Published:2022 Issue: Volume: Page:1-15
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Wang HaiTao¹,Chen Jie¹^ORCID,Huang ZhiXiang¹^ORCID,Li Bing¹,Lv JianMing¹,Xi JingMin¹,Wu BoCai²,Zhang Jun³^ORCID,Wu ZhongCheng³

Affiliation:

1. Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Electronics and Information Engineering, Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, China

2. 38th Research Institute of China Electronics Technology Group Corporation, Hefei, China

3. Hefei Institute of Physical Science, Chinese Academy of Sciences, Hefei, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Anhui Province

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/4358928/09945665.pdf?arnumber=9945665

Reference68 articles.

1. Cluster Regularized Extreme Learning Machine for Detecting Mixed-Type Distraction in Driving

2. Recognition of driving postures by multiwavelet transform and multilayer perceptron classifier

3. Driver Distraction Detection Using Semi-Supervised Machine Learning

4. Understanding head and hand activities and coordination in naturalistic driving videos

5. Driver Distracted Behavior Detection Technology with YOLO-Based Deep Learning Networks

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