Car Traffic Sign Recognizer Using Convolutional Neural Network CNN

被引:5
|
作者
Lodhi, Abhay [1 ]
Singhal, Sagar [2 ]
Massoudi, Massoud [3 ]
机构
[1] Delhi Technol Univ, Comp Sci Dept, Delhi, India
[2] Delhi Technol Univ, Elect & Commun Dept, Delhi, India
[3] Delhi Technol Univ, Delhi, India
关键词
Convolution neural network; Adam optimizer; Traffic Sign;
D O I
10.1109/ICICT50816.2021.9358594
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Acknowledgment of traffic signs vary significantly in numerous applications, for example, in self-driving vehicle/driverless vehicle, traffic planning and traffic observation. Traffic Sign Recognition (TSR) framework is a segment of Driving Assistance System (ADAS). The TSR framework helps the drivers in safe driving as street signs give significant data of the street The car business has built up a great deal and a portion of the organizations are attempting to assemble self-sufficient vehicles and in which traffic sign acknowledgment is one of the significant factors to be thought of. To perceive the traffic signs, a model utilizing convolutional neural network is fabricated and this model will perceive the traffic signs. This model can likewise be utilized in typical vehicles to caution the driver about traffic signs through content identification.
引用
收藏
页码:577 / 582
页数:6
相关论文
共 50 条
  • [42] Temporal Classification Error Compensation of Convolutional Neural Network for Traffic Sign Recognition
    Yoon, Seungjong
    Kim, Eungtae
    Journal of Physics: Conference Series, 2017, 806 (01):
  • [43] Temporal Classification Error Compensation of Convolutional Neural Network for Traffic Sign Recognition
    Yoon, Seungjong
    Kim, Eungtae
    2017 INTERNATIONAL CONFERENCE ON CONTROL ENGINEERING AND ARTIFICIAL INTELLIGENCE (CCEAI 2017), 2017, 806
  • [44] Traffic Sign Recognition with Convolutional Neural Network Based on Max Pooling Positions
    Qian, Rongqiang
    Yue, Yong
    Coenen, Frans
    Zhang, Bailing
    2016 12TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD), 2016, : 578 - 582
  • [45] Experimental Design of a Quantum Convolutional Neural Network Solution for Traffic Sign Recognition
    Cox, Dylan
    INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 1, 2023, 542 : 605 - 617
  • [46] A Convolutional Neural Network-Based Method for Small Traffic Sign Detection
    Zhou S.
    Zhi X.
    Liu D.
    Ning H.
    Jiang L.
    Shi F.
    Tongji Daxue Xuebao/Journal of Tongji University, 2019, 47 (11): : 1626 - 1632
  • [47] Robust Chinese Traffic Sign Detection and Recognition with Deep Convolutional Neural Network
    Qian, Rongqiang
    Zhang, Bailing
    Yue, Yong
    Wang, Zhao
    Coenen, Frans
    2015 11TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC), 2015, : 791 - 796
  • [48] A Traffic Sign Image Recognition and Classification Approach Based on Convolutional Neural Network
    Liu Shangzhen
    2019 11TH INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION (ICMTMA 2019), 2019, : 408 - 411
  • [49] Traffic Sign Detection with Convolutional Neural Networks
    Peng, Evan
    Chen, Feng
    Song, Xinkai
    COGNITIVE SYSTEMS AND SIGNAL PROCESSING, ICCSIP 2016, 2017, 710 : 214 - 224
  • [50] Butterfly Species Identification Using Convolutional Neural Network (CNN)
    Arzar, Nur Nabila Kamaron
    Sabri, Nurbaity
    Johari, Nur Farahin Mohd
    Shari, Anis Amilah
    Noordin, Mohd Rahmat Mohd
    Ibrahim, Shafaf
    2019 IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC CONTROL AND INTELLIGENT SYSTEMS (I2CACIS), 2019, : 221 - 224