Traffic sign classification using CNN and detection using faster-RCNN and YOLOV4 [PDF]
Heliyon, 2022 Autonomous driving cars are becoming popular everywhere and the need for a robust traffic sign recognition system that ensures safety by recognizing traffic signs accurately and fast is increasing.
Njayou Youssouf
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Improving Performance of the PRYSTINE Traffic Sign Classification by Using a Perturbation-Based Explainability Approach [PDF]
Journal of Imaging, 2022 Model understanding is critical in many domains, particularly those involved in high-stakes decisions, e.g., medicine, criminal justice, and autonomous driving.
Kaspars Sudars +2 more
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Road traffic sign detection and classification [PDF]
IEEE Transactions on Industrial Electronics, 1997 A vision-based vehicle guidance system for road vehicles can have three main roles: (1) road detection; (2) obstacle detection; and (3) sign recognition.
Armingol Moreno, José María +3 more
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Traffic Sign Detection and Classification on the Austrian Highway Traffic Sign Data Set
Data, 2023 Advanced Driver Assistance Systems rely on automated traffic sign recognition. Today, Deep Learning methods outperform other approaches in terms of accuracy and processing time; however, they require vast and well-curated data sets for training.
Alexander Maletzky +4 more
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Classification of rare traffic signs [PDF]
Компьютерная оптика, 2020 The paper studies the possibility of using neural networks for the classification of objects that are few or absent at all in the training set. The task is illustrated by the example of classification of rare traffic signs.
Boris Faizov +3 more
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Classification with NormalBoost: Case Study Traffic Sign Classification
Journal of Intelligent Systems, 2012 NormalBoost is a new boosting algorithm which is capable of classifying a multi-dimensional binary class dataset. It adaptively combines several weak classifiers to form a strong classifier. Unlike many boosting algorithms which have high computation and
Fleyeh Hasan, Davami Erfan
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Dense-RefineDet for Traffic Sign Detection and Classification [PDF]
Sensors, 2020 Detecting and classifying real-life small traffic signs from large input images is difficult due to their occupying fewer pixels relative to larger targets. To address this challenge, we proposed a deep-learning-based model (Dense-RefineDet) that applies
Chang Sun +3 more
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The Bangladesh road traffic sign dataset in real-world images for traffic sign recognitionzenodo [PDF]
Data in BriefTraffic sign detection and classification have significant impacts in the field of automated driving system, traffic management, driver assistance system, to detect traffic rules violations etc.
Md. Ariful Islam, Dewan Md. Farid
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Attention to detail: A conditional multi-head transformer for traffic sign recognition. [PDF]
PLoS ONEThe challenge of traffic sign detection and recognition for driving vehicles has become more critical with recent advances in autonomous and assisted driving technologies.
Isra Naz +5 more
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Traffic Sign Detection and Quality Assessment Using YOLOv8 in Daytime and Nighttime Conditions [PDF]
SensorsTraffic safety remains a pressing global concern, with traffic signs playing a vital role in regulating and guiding drivers. However, environmental factors like lighting and weather often compromise their visibility, impacting human drivers and ...
Ziyad N. Aldoski, Csaba Koren
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