Results 41 to 50 of about 530,497 (220)
, 2013 {"references": ["J. Cooper, K. Stafford, P. Owlett and J. Mitchell. CSS Street Lighting\nProject SL5/2007. Published Project Report PPR382. Review of the\nlighting requirement for traffic signs and bollards.", "Jennie Oxley and Brian Fildes. Monash University Accident Research\nCentre.
A. Gutiérrez +4 more
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Self-supervised few-shot learning for real-time traffic sign classification
IJAIN (International Journal of Advances in Intelligent Informatics)Although supervised approaches for traffic sign classification have demonstrated excellent performance, they are limited to classifying several traffic signs defined in the training dataset. This prevents them from being applied to different domains, i.e.
Anh-Khoa Tho Nguyen +3 more
doaj +1 more source
Simultaneous Traffic Sign Detection and Boundary Estimation using Convolutional Neural Network
, 2018 We propose a novel traffic sign detection system that simultaneously estimates the location and precise boundary of traffic signs using convolutional neural network (CNN).
Kim, Kang, Lee, Hee Seok
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Vehicle-induced loads on traffic sign panels [PDF]
, 2003 The determination of the loads on traffic sign panels in the current standards does not, in general, take into account the vehicle-induced loads, as explained by Quinn, Baker and Wright (QBW in what follows) (J. Wind Eng. Ind. Aerodyn. 89 (2001) 831). On
Baker, J. +3 more
core +2 more sources
Did You Miss the Sign? A False Negative Alarm System for Traffic Sign Detectors
, 2019 Object detection is an integral part of an autonomous vehicle for its safety-critical and navigational purposes. Traffic signs as objects play a vital role in guiding such systems.
Dayoub, Feras +2 more
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Traffic Sign Detection Based on Saliency Map and Fourier Descriptor [PDF]
Jisuanji gongcheng, 2017 Aiming at the problems in traffic sign detection process,such as that traffic sign shows dimensional changes,rotation distortion,projection distortion or the sign is partially occluded,in this paper,a traffic sign detection algorithm based on saliency ...
YU Chaochao,HOU Jin,HOU Changzheng
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Research on traffic sign recognition method based on multi-scale convolution neural network
Xibei Gongye Daxue Xuebao, 2021 In order to accurately identify the traffic sign information under different road conditions, an improved deep learning method based on Faster RCNN model is proposed.
doaj +1 more source
VSSA-NET: Vertical Spatial Sequence Attention Network for Traffic Sign Detection
, 2019 Although traffic sign detection has been studied for years and great progress has been made with the rise of deep learning technique, there are still many problems remaining to be addressed.
IEEE +8 more
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TRAFFIC SIGN DESCRIPTION SYSTEM
international journal of engineering technology and management sciences, 2022 Traffic Sign Recognition is used to give an audio description to a image sign traffic signs and thus warn a driver, and command or prohibit certain actions. A fast real-time and robust automatic traffic sign detection and recognition can support and disburden the driver and significantly increase driving safety and comfort.
null B.GNANESWAR SAI +4 more
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Influence of Driver's Experience on Textual Traffic Sign Efficiency Depending on Visibility
Promet (Zagreb), 2012 The research objective is to study the influence of thedriver's experience on the efficiency of the textual traffic sign dependingon the visibility, that is on the weather conditions.
Senka Pašagić +2 more
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