Traffic sign Detection using CNN
International Journal of Engineering and Advanced Technology, 2021 Lane Detection and Traffic sign detection are the essential components in ADAS .Although there has been significant quantity of analysis dedicated to the detection of lane detection and sign detection in the past, there is still need robustness in the system.
K. Mirunalini, Dr.Vasantha Kalyani David
openaire +1 more source
A traffic sign detection model based on coordinate attention - bidirectional feature pyramid network
Shenzhen Daxue xuebao. Ligong ban, 2023 In the field of autonomous driving, the correct detection of traffic signs can provide important information for environmental perception. To address the low recognition rate and misdetection and missed detection issues of various traffic signs, we ...
LANG Binke +3 more
doaj +1 more source
A Real-Time Chinese Traffic Sign Detection Algorithm Based on Modified YOLOv2
Algorithms, 2017 Traffic sign detection is an important task in traffic sign recognition systems. Chinese traffic signs have their unique features compared with traffic signs of other countries.
Jianming Zhang +3 more
doaj +1 more source
Traffic sign detection for U.S. roads:Remaining challenges and a case for tracking [PDF]
, 2014 — Traffic sign detection is crucial in intelligent vehi-cles, no matter if one’s objective is to develop Advanced Driver Assistance Systems or autonomous cars.
Liu, Dongran +2 more
core +3 more sources
Two algorithms for detection of mutually occluding traffic signs [PDF]
, 2012 The robust identification of the traffic signs represents the first and one of the most important steps in the development of a traffic sign recognition (TSR) system.
Bui, Thanh +4 more
core +1 more source
Round Traffic Sign Detection Algorithm
Journal of Physics: Conference Series, 2022 Abstract Traffic signs are an important part of autonomous driving and intelligent transportation. It provides instructions for pedestrians and vehicles and is critical to road traffic safety. However, existing detection algorithms cannot achieve real-time high-precision detection.
Yinrong Huang, Bing Wang, Xiemin Yuan
openaire +1 more source
A Cascaded R-CNN With Multiscale Attention and Imbalanced Samples for Traffic Sign Detection
IEEE Access, 2020 In recent years, the deep learning is applied to the field of traffic sign detection methods which achieves excellent performance. However, there are two main challenges in traffic sign detection to be solve urgently. For one thing, some traffic signs of
Jianming Zhang +4 more
doaj +1 more source
EDGE DETECTION TECHNIQUE BASED ON BILATERAL FILTERING AND ITERATIVE THRESHOLD SELECTION ALGORITHM AND TRANSFER LEARNING FOR TRAFFIC SIGN RECOGNITION [PDF]
Scientific Journal of Silesian University of Technology. Series Transport, 2023 The traffic sign identification and recognition system (TSIRS) is an essential component for autonomous vehicles to succeed. The TSIRS helps to collect and provide helpful information for autonomous driving systems.
Milind PARSE, Dhanya PRAMOD
doaj +1 more source
An optimization approach for localization refinement of candidate traffic signs [PDF]
, 2017 We propose a localisation refinement approach for candidate traffic signs. Previous traffic sign localisation approaches which place a bounding rectangle around the sign do not always give a compact bounding box, making the subsequent classification ...
Hu, Shimin +3 more
core +2 more sources
Integrated Feature Pyramid Network With Feature Aggregation for Traffic Sign Detection
IEEE Access, 2021 Traffic sign detection is a critical task in the visual system of the Advanced Driver Assistance System (ADAS) and the Automated Driving System (ADS). Although the general object detection has achieved promising results by using Feature Pyramid Network ...
Qing Tang, Ge Cao, Kang-Hyun Jo
doaj +1 more source