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A Graph-Based Algorithm for Supervised Image Classification

  • Ke Du
  • Jinlong Liu
  • Xingrui Zhang
  • Jianying Feng
  • Yudong Guan
  • Stéphane Domas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10861)

Abstract

Manifold learning is a main stream research track used for dimensionality reduction as a method to select features. Many variants have been proposed with good performance. A novel graph-based algorithm for supervised image classification is introduced in this paper. It makes the use of graph embedding to increase the recognition accuracy. The proposed algorithm is tested on four benchmark datasets of different types including scene, face and object. The experimental results show the validity of our solution by comparing it with several other tested algorithms.

Keywords

Graph-based Supervised learning Image classification 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Ke Du
    • 1
  • Jinlong Liu
    • 2
  • Xingrui Zhang
    • 2
  • Jianying Feng
    • 2
  • Yudong Guan
    • 2
  • Stéphane Domas
    • 1
  1. 1.FEMTO-ST Institute, UMR 6174 CNRS, University of Bourgogne Franche-ComtéBelfortFrance
  2. 2.School of Electronics and Information EngineeringHarbin Institute of TechnologyHarbinChina

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