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Adaptive Ensemble Clustering for Image Segmentation in Remote Sensing

  • Tingting Yao
  • Chang Liu
  • Zhian Deng
  • Xiaoming Liu
  • Jiacheng Liu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 463)

Abstract

Image segmentation is a fundamental computer vision task. Although many approaches have been proposed, obtaining accurate results in some special applications are still not easy. In this paper, we propose a novel image segmentation method for remote sensing based on adaptive cluster ensemble learning. The clustering parameter of each image is calculated with affinity propagation automatically. Then, multiple clusterers are trained separately and the predictions of them are combined under the ensemble learning framework. In this way, the robustness of each clusterer could be enhanced. Experimental results demonstrate the effectiveness of our proposed method.

Keywords

Ensemble learning Affinity propagation Remote sensing Image segmentation 

Notes

Acknowledgments

This work was supported by the National Natural Science Foundation of China (61301132), the Natural Science Foundation of Liaoning Province (201601065), the National Key Technology R&D Program (2015BAG20B02) and the Fundamental Research Funds for the Central Universities (3132017129, 32016347).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Tingting Yao
    • 1
  • Chang Liu
    • 1
  • Zhian Deng
    • 1
  • Xiaoming Liu
    • 1
  • Jiacheng Liu
    • 2
  1. 1.Dalian Maritime UniversityDalianChina
  2. 2.Northeastern UniversityBostonUSA

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