Ensemble Image Classification Method Based on Genetic Image Network

  • Shiro Nakayama
  • Shinichi Shirakawa
  • Noriko Yata
  • Tomoharu Nagao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6021)


Automatic construction method for image classification algorithms have been required. Genetic Image Network for Image Classification (GIN-IC) is one of the methods that construct image classification algorithms automatically, and its effectiveness has already been proven. In our study, we try to improve the performance of GIN-IC with AdaBoost algorithm using GIN-IC as weak classifiers to complement with each other. We apply our proposed method to three types of image classification problems, and show the results in this paper. In our method, discrimination rates for training images and test images improved in the experiments compared with the previous method GIN-IC.


Particle Swarm Optimization Test Image Training Image Output Node Texture Image 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Shiro Nakayama
    • 1
  • Shinichi Shirakawa
    • 1
  • Noriko Yata
    • 1
  • Tomoharu Nagao
    • 1
  1. 1.Graduate School of Environment and Information SciencesYokohama National UniversityKanagawaJapan

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