Spectral-Spatial Classification of Hyperspectral Image Based on Kernel Extreme Learning Machine

@article{Chen2014SpectralSpatialCO,
  title={Spectral-Spatial Classification of Hyperspectral Image Based on Kernel Extreme Learning Machine},
  author={Chen Chen and Wei Li and Hongjun Su and Kui Liu},
  journal={Remote Sensing},
  year={2014},
  volume={6},
  pages={5795-5814}
}
Extreme learning machine (ELM) is a single-layer feedforward neural network based classifier that has attracted significant attention in computer vision and pattern recognition due to its fast learning speed and strong generalization. In this paper, we propose to integrate spectral-spatial information for hyperspectral image classification and exploit the benefits of using spatial features for the kernel based ELM (KELM) classifier. Specifically, Gabor filtering and multihypothesis (MH… CONTINUE READING
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Kernel-based extreme learning machine for remote-sensing image classification

  • M. Pal, A. E. Maxwell, T. A. Warner
  • Remote Sens. Lett. 2013,
  • 2013
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