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Recognition and Counting of Motorcycles by Fusing Support Vector Machine and Deep Learning

  • Tzung-Pei HongEmail author
  • Yu-Chiao Yang
  • Ja-Hwung Su
  • Shyue-Liang Wang
Conference paper
  • 483 Downloads
Part of the Communications in Computer and Information Science book series (CCIS, volume 1013)

Abstract

In recent years, rapid growth of motorcycles enables a large number of traffic accidents. Hence, how to manage the traffic flow has been a hot topic. In this paper, we propose a method for recognizing and counting the motorcycles by integrating the support vector machine (SVM) and convolutional neural network (CNN). In this work, the CNN is first adopted to generate the implicit features, and then the SVM is trained based on the implicit features and tested for unknown images. The experimental results reveal the proposed method can achieve low error rates in counting motorcycles.

Keywords

Convolutional neural network Support vector machine Motorcycle counting Motorcycle recognition 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Tzung-Pei Hong
    • 1
    • 2
    Email author
  • Yu-Chiao Yang
    • 1
  • Ja-Hwung Su
    • 3
  • Shyue-Liang Wang
    • 4
  1. 1.Department of Computer Science and Information EngineeringNational University of KaohsiungKaohsiungTaiwan
  2. 2.Department of Computer Science and EngineeringNational Sun Yat-Sen UniversityKaohsiungTaiwan
  3. 3.Department of Information ManagementCheng Shiu UniversityKaohsiungTaiwan
  4. 4.Department of Information ManagementNational University of KaohsiungKaohsiungTaiwan

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