D‐patches: effective traffic sign detection with occlusion handling

Author:

Rehman Yawar1,Riaz Irfan1,Fan Xue1,Shin Hyunchul1

Affiliation:

1. Department of Electronics and Communication EngineeringHanyang UniversityAnsan426‐791Korea

Publisher

Institution of Engineering and Technology (IET)

Subject

Computer Vision and Pattern Recognition,Software

Reference29 articles.

1. Vision‐based traffic sign detection and analysis for intelligent driver assistance systems: perspectives and survey;Mogelmose A.;IEEE TITS,2012

2. Fast traffic sign recognition via high‐contrast region extraction and extended sparse representation;Liu C.;iIEEE TITS,2016

3. Real‐time detection and recognition of road traffic signs;Greenhalgh J.;IEEE TITS,2012

4. Liang M. Yuan M. Hu X. et al: ‘Traffic sign detection by ROI extraction and histogram features‐based recognition’.IJCNN 2013 pp.1–8

5. Wang G. Reney G. Wu Z. et al: ‘A robust coarse‐to‐fine traffic sign detection method’.IJCNN 2013 pp.754–758

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1. Indian TSR for partial occlusion using GDNN;Multimedia Tools and Applications;2023-07-27

2. Deep Learning-Based Traffic Sign Identification Using Multi-Scale Feature Fusion;2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN);2023-07-04

3. Traffic Sign Recognition with Deep Learning: Vegetation Occlusion Detection in Brazilian Environments;Sensors;2023-06-26

4. A review of occluded objects detection in real complex scenarios for autonomous driving;Green Energy and Intelligent Transportation;2023-06

5. Cognition based Recognition of Partially Occluded Traffic Signs;Scientia Iranica;2022-02-14

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