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
来源
PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT 2021) | 2021年
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
  • [31] Traffic sign detection and recognition based on pyramidal convolutional networks
    Liang, Zhenwen
    Shao, Jie
    Zhang, Dongyang
    Gao, Lianli
    NEURAL COMPUTING & APPLICATIONS, 2020, 32 (11): : 6533 - 6543
  • [32] Plant Disease Detection Using Sequential Convolutional Neural Network
    Tripathi, Anshul
    Chourasia, Uday
    Dixit, Priyanka
    Chang, Victor
    INTERNATIONAL JOURNAL OF DISTRIBUTED SYSTEMS AND TECHNOLOGIES, 2022, 13 (01)
  • [33] Fault Diagnosis of Induction Motor Using Convolutional Neural Network
    Lee, Jong-Hyun
    Pack, Jae-Hyung
    Lee, In-Soo
    APPLIED SCIENCES-BASEL, 2019, 9 (15):
  • [34] PEAK DETECTION AND BASELINE CORRECTION USING A CONVOLUTIONAL NEURAL NETWORK
    Schmidt, Mikkel N.
    Alstrom, Tommy S.
    Svendstorp, Marcus
    Larsen, Jan
    2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2019, : 2757 - 2761
  • [35] Detection and classification of epilepsy using hybrid convolutional neural network
    Sabarivani, A.
    Ramadevi, R.
    CONCURRENT ENGINEERING-RESEARCH AND APPLICATIONS, 2022, 30 (03): : 253 - 261
  • [36] Measurement of EDMed surfaces roughness using convolutional neural network
    Kumar, Amit
    Pradhan, Mohan Kumar
    Das, Raja
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART E-JOURNAL OF PROCESS MECHANICAL ENGINEERING, 2023,
  • [37] Automated Pain Severity Detection Using Convolutional Neural Network
    Semwal, Ashish
    Londhe, Narendra D.
    PROCEEDINGS OF THE 2018 INTERNATIONAL CONFERENCE ON COMPUTATIONAL TECHNIQUES, ELECTRONICS AND MECHANICAL SYSTEMS (CTEMS), 2018, : 66 - 70
  • [38] Face Recognition Using Gabor Filter And Convolutional Neural Network
    Kinnikar, Ashwini
    Husain, Moula
    Meena, S. M.
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INFORMATICS AND ANALYTICS (ICIA' 16), 2016,
  • [39] Flood susceptibility mapping using convolutional neural network frameworks
    Wang, Yi
    Fang, Zhice
    Hong, Haoyuan
    Peng, Ling
    JOURNAL OF HYDROLOGY, 2020, 582
  • [40] Predictive Maintenance in Aerospace Industry Using Convolutional Neural Network
    Pebrianti, Dwi
    Khalani, Zulhakim
    Rusdah
    Bayuaji, Luhur
    9TH INTERNATIONAL CONFERENCE ON MECHATRONICS ENGINEERING, ICOM 2024, 2024, : 157 - 162