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Search Results (13)
  • Open Access

    ARTICLE

    A Hybrid Feature Fusion Traffic Sign Detection Algorithm Based on YOLOv7

    Bingyi Ren1,4, Juwei Zhang2,3,4,*, Tong Wang2,4

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1425-1440, 2024, DOI:10.32604/cmc.2024.052667 - 18 July 2024

    Abstract Autonomous driving technology has entered a period of rapid development, and traffic sign detection is one of the important tasks. Existing target detection networks are difficult to adapt to scenarios where target sizes are seriously imbalanced, and traffic sign targets are small and have unclear features, which makes detection more difficult. Therefore, we propose a Hybrid Feature Fusion Traffic Sign detection algorithm based on YOLOv7 (HFFT-YOLO). First, a self-attention mechanism is incorporated at the end of the backbone network to calculate feature interactions within scales; Secondly, the cross-scale fusion part of the neck introduces a… More >

  • Open Access

    ARTICLE

    A New Speed Limit Recognition Methodology Based on Ensemble Learning: Hardware Validation

    Mohamed Karray1,*, Nesrine Triki2,*, Mohamed Ksantini2

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 119-138, 2024, DOI:10.32604/cmc.2024.051562 - 18 July 2024

    Abstract Advanced Driver Assistance Systems (ADAS) technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the road. Traffic Sign Recognition System (TSRS) is one of the most important components of ADAS. Among the challenges with TSRS is being able to recognize road signs with the highest accuracy and the shortest processing time. Accordingly, this paper introduces a new real time methodology recognizing Speed Limit Signs based on a trio of developed modules. Firstly, the Speed Limit Detection (SLD) module uses… More >

  • Open Access

    ARTICLE

    C2Net-YOLOv5: A Bidirectional Res2Net-Based Traffic Sign Detection Algorithm

    Xiujuan Wang1, Yiqi Tian1,*, Kangfeng Zheng2, Chutong Liu3

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1949-1965, 2023, DOI:10.32604/cmc.2023.042224 - 29 November 2023

    Abstract Rapid advancement of intelligent transportation systems (ITS) and autonomous driving (AD) have shown the importance of accurate and efficient detection of traffic signs. However, certain drawbacks, such as balancing accuracy and real-time performance, hinder the deployment of traffic sign detection algorithms in ITS and AD domains. In this study, a novel traffic sign detection algorithm was proposed based on the bidirectional Res2Net architecture to achieve an improved balance between accuracy and speed. An enhanced backbone network module, called C2Net, which uses an upgraded bidirectional Res2Net, was introduced to mitigate information loss in the feature extraction… More >

  • Open Access

    ARTICLE

    Traffic Sign Recognition for Autonomous Vehicle Using Optimized YOLOv7 and Convolutional Block Attention Module

    P. Kuppusamy1,*, M. Sanjay1, P. V. Deepashree1, C. Iwendi2

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 445-466, 2023, DOI:10.32604/cmc.2023.042675 - 31 October 2023

    Abstract The infrastructure and construction of roads are crucial for the economic and social development of a region, but traffic-related challenges like accidents and congestion persist. Artificial Intelligence (AI) and Machine Learning (ML) have been used in road infrastructure and construction, particularly with the Internet of Things (IoT) devices. Object detection in Computer Vision also plays a key role in improving road infrastructure and addressing traffic-related problems. This study aims to use You Only Look Once version 7 (YOLOv7), Convolutional Block Attention Module (CBAM), the most optimized object-detection algorithm, to detect and identify traffic signs, and… More >

  • Open Access

    ARTICLE

    Multi-Objective Optimization of Traffic Signal Timing at Typical Junctions Based on Genetic Algorithms

    Zeyu Zhang1, Han Zhu1, Wei Zhang1, Zhiming Cai2,*, Linkai Zhu2, Zefeng Li2

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1901-1917, 2023, DOI:10.32604/csse.2023.039395 - 28 July 2023

    Abstract With the rapid development of urban road traffic and the increasing number of vehicles, how to alleviate traffic congestion is one of the hot issues that need to be urgently addressed in building smart cities. Therefore, in this paper, a nonlinear multi-objective optimization model of urban intersection signal timing based on a Genetic Algorithm was constructed. Specifically, a typical urban intersection was selected as the research object, and drivers’ acceleration habits were taken into account. What’s more, the shortest average delay time, the least average number of stops, and the maximum capacity of the intersection… More >

  • Open Access

    ARTICLE

    Pre-Locator Incorporating Swin-Transformer Refined Classifier for Traffic Sign Recognition

    Qiang Luo1, Wenbin Zheng1,2,*

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2227-2246, 2023, DOI:10.32604/iasc.2023.040195 - 21 June 2023

    Abstract In the field of traffic sign recognition, traffic signs usually occupy very small areas in the input image. Most object detection algorithms directly reduce the original image to a specific size for the input model during the detection process, which leads to the loss of small object information. Additionally, classification tasks are more sensitive to information loss than localization tasks. This paper proposes a novel traffic sign recognition approach, in which a lightweight pre-locator network and a refined classification network are incorporated. The pre-locator network locates the sub-regions of the traffic signs from the original… More >

  • Open Access

    ARTICLE

    Traffic Sign Detection with Low Complexity for Intelligent Vehicles Based on Hybrid Features

    Sara Khalid1, Jamal Hussain Shah1,*, Muhammad Sharif1, Muhammad Rafiq2, Gyu Sang Choi3,*

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 861-879, 2023, DOI:10.32604/cmc.2023.035595 - 08 June 2023

    Abstract Globally traffic signs are used by all countries for healthier traffic flow and to protect drivers and pedestrians. Consequently, traffic signs have been of great importance for every civilized country, which makes researchers give more focus on the automatic detection of traffic signs. Detecting these traffic signs is challenging due to being in the dark, far away, partially occluded, and affected by the lighting or the presence of similar objects. An innovative traffic sign detection method for red and blue signs in color images is proposed to resolve these issues. This technique aimed to devise… More >

  • Open Access

    ARTICLE

    A Deep Learning Model of Traffic Signs in Panoramic Images Detection

    Kha Tu Huynh1, Thi Phuong Linh Le1, Muhammad Arif2, Thien Khai Tran3,*

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 401-418, 2023, DOI:10.32604/iasc.2023.036981 - 29 April 2023

    Abstract To pursue the ideal of a safe high-tech society in a time when traffic accidents are frequent, the traffic signs detection system has become one of the necessary topics in recent years and in the future. The ultimate goal of this research is to identify and classify the types of traffic signs in a panoramic image. To accomplish this goal, the paper proposes a new model for traffic sign detection based on the Convolutional Neural Network for comprehensive traffic sign classification and Mask Region-based Convolutional Neural Networks (R-CNN) implementation for identifying and extracting signs in More >

  • Open Access

    ARTICLE

    Numerical Simulation Study of Vibration Characteristics of Cantilever Traffic Signal Support Structure under Wind Environment

    Meng Zhang1, Zhichao Zhou1, Guifeng Zhao1,*, Fangfang Wang2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 673-698, 2023, DOI:10.32604/cmes.2022.021463 - 24 August 2022

    Abstract Computational fluid dynamics (CFD) and the finite element method (FEM) are used to investigate the wind-driven dynamic response of cantilever traffic signal support structures as a whole. By building a finite element model with the same scale as the actual structure and performing modal analysis, a preliminary understanding of the dynamic properties of the structure is obtained. Based on the two-way fluid-structure coupling calculation method, the wind vibration response of the structure under different incoming flow conditions is calculated, and the vibration characteristics of the structure are analyzed through the displacement time course data of… More >

  • Open Access

    ARTICLE

    Identification and Acknowledgment of Programmed Traffic Sign Utilizing Profound Convolutional Neural Organization

    P. Vigneshwaran1,*, N. Prasath1, M. Islabudeen2, A. Arun1, A. K. Sampath2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1527-1543, 2023, DOI:10.32604/iasc.2023.028444 - 19 July 2022

    Abstract Traffic signs are basic security workplaces making the rounds, which expects a huge part in coordinating busy time gridlock direct, ensuring the prosperity of the road and dealing with the smooth segment of vehicles and individuals by walking, etc. As a segment of the clever transportation structure, the acknowledgment of traffic signs is basic for the driving assistance system, traffic sign upkeep, self-administering driving, and various spaces. There are different assessments turns out achieved for traffic sign acknowledgment in the world. However, most of the works are only for explicit arrangements of traffic signs, for… More >

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