ReviewSensors (Basel, Switzerland)2019
Vision-Based Traffic Sign Detection and Recognition Systems: Current Trends and Challenges.
Review in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Analysis of AWS Rekognition and Azure Custom Vision Performance in Parking Sign Recognition.Sensors (Basel, Switzerland) · 2025Article
- Traffic Sign Detection and Quality Assessment Using YOLOv8 in Daytime and Nighttime Conditions.Sensors (Basel, Switzerland) · 2025Article
- Attention to detail: A conditional multi-head transformer for traffic sign recognition.PloS one · 2025Article
- A New Multi-Branch Convolutional Neural Network and Feature Map Extraction Method for Traffic Congestion Detection.Sensors (Basel, Switzerland) · 2024Article
- Traffic Sign Recognition with Deep Learning: Vegetation Occlusion Detection in Brazilian Environments.Sensors (Basel, Switzerland) · 2023Article
- Equirectangular Image Data Detection, Segmentation and Classification of Varying Sized Traffic Signs: A Comparison of Deep Learning Methods.Sensors (Basel, Switzerland) · 2023Article
- TSR-YOLO: A Chinese Traffic Sign Recognition Algorithm for Intelligent Vehicles in Complex Scenes.Sensors (Basel, Switzerland) · 2023Article
- Improvement of driver night vision in foggy environments by structured light projection.Heliyon · 2022Article
- Hierarchical Novelty Detection for Traffic Sign Recognition.Sensors (Basel, Switzerland) · 2022Article
- A Novel Lightweight Real-Time Traffic Sign Detection Integration Framework Based on YOLOv4.Entropy (Basel, Switzerland) · 2022Article
- Sensors on the Move: Onboard Camera-Based Real-Time Traffic Alerts Paving the Way for Cooperative Roads.Sensors (Basel, Switzerland) · 2021Article
- Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments.Sensors (Basel, Switzerland) · 2020Article
- Vehicular Traffic Congestion Classification by Visual Features and Deep Learning Approaches: A Comparison.Sensors (Basel, Switzerland) · 2019Article
- Improved Traffic Sign Detection and Recognition Algorithm for Intelligent Vehicles.Sensors (Basel, Switzerland) · 2019Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The automatic traffic sign detection and recognition (TSDR) system is very important research in the development of advanced driver assistance systems (ADAS). Investigations on vision-based TSDR have received substantial interest in the research community, which is mainly motivated by three factors, which are detection, tracking and classification. During the last decade, a substantial number of techniques have been reported for TSDR. This paper provides a comprehensive survey on traffic sign detection, tracking and classification. The details of algorithms, methods and their specifications on detection, tracking and classification are investigated and summarized in the tables along with the corresponding key references. A comparative study on each section has been provided to evaluate the TSDR data, performance metrics and their availability. Current issues and challenges of the existing technologies are illustrated with brief suggestions and a discussion on the progress of driver assistance system research in the future. This review will hopefully lead to increasing efforts towards the development of future vision-based TSDR system.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.