Portable convolution neural networks for traffic sign recognition in intelligent transportation systems

Junhao ZHOU, Hong Ning DAI, Hao WANG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

2 Citations (Scopus)

Abstract

Deep convolutional neural networks (CNN) have the strength in traffic-sign classification in terms of high accuracy. However, CNN models usually contains multiple layers with a large number of parameters consequently leading to a large model size. The bulky model size of CNN models prevents them from the wide deployment in mobile and portable devices in Intelligent Transportation Systems. In this paper, we design and develop a portable convolutional neural network (namely portable CNN) structure used for traffic-sign classification. This portable CNN model contains a stacked convolutional structure consisting of factorization and compression modules. We conducted extensive experiments to evaluate the performance of the proposed Portable CNN model. Experimental results show that our model has the advantages of smaller model size while maintaining high classification accuracy, compared with conventional CNN models.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE International Congress on Cybermatics
Subtitle of host publication12th IEEE International Conference on Internet of Things, 15th IEEE International Conference on Green Computing and Communications, 12th IEEE International Conference on Cyber, Physical and Social Computing and 5th IEEE International Conference on Smart Data, iThings/GreenCom/CPSCom/SmartData 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages52-57
Number of pages6
ISBN (Electronic)9781728129808
DOIs
Publication statusPublished - Jul 2019
Externally publishedYes
Event12th IEEE International Conference on Internet of Things, 15th IEEE International Conference on Green Computing and Communications, 12th IEEE International Conference on Cyber, Physical and Social Computing and 5th IEEE International Conference on Smart Data, iThings/GreenCom/CPSCom/SmartData 2019 - Atlanta, United States
Duration: 14 Jul 201917 Jul 2019

Publication series

NameProceedings - 2019 IEEE International Congress on Cybermatics: 12th IEEE International Conference on Internet of Things, 15th IEEE International Conference on Green Computing and Communications, 12th IEEE International Conference on Cyber, Physical and Social Computing and 5th IEEE International Conference on Smart Data, iThings/GreenCom/CPSCom/SmartData 2019

Conference

Conference12th IEEE International Conference on Internet of Things, 15th IEEE International Conference on Green Computing and Communications, 12th IEEE International Conference on Cyber, Physical and Social Computing and 5th IEEE International Conference on Smart Data, iThings/GreenCom/CPSCom/SmartData 2019
Country/TerritoryUnited States
CityAtlanta
Period14/07/1917/07/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

  • Convolutional neural networks
  • Factorization
  • Intelligent Transportation Systems
  • Model Compression
  • Portable

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