Opening the black box of neural networks for remote sensing image classification

@inproceedings{Qiu2004OpeningTB,
  title={Opening the black box of neural networks for remote sensing image classification},
  author={Feng Qiu},
  year={2004}
}
Neural networks, which make no assumption about data distribution, have achieved improved image classification results compared to traditional methods. Unfortunately, a neural network is generally perceived as being a ‘black box’. It is extremely difficult to document how specific classification decisions are reached. Fuzzy systems, on the other hand, have the capability to represent classification decisions explicitly in the form of fuzzy ‘if-then’ rules. However, the construction of a… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 37 references

Self-Organization and Associate Memory, 3rd edn (New York: Springer-Verlag)

  • T. KOHONEN
  • 1989
Highly Influential
6 Excerpts

Foundation of Neuro-Fuzzy Systems (Chichester

  • D. NAUCK, F. KLAWOON, R. KRUSE
  • 1997
Highly Influential
3 Excerpts

Introductory Digital Image Processing: A remote sensing perspective (Upper Saddle River, NJ: Prentice-Hall)

  • J. R. JENSEN
  • 1996
Highly Influential
4 Excerpts

Remote Sensing of the Environment: An Earth resource perspective (Upper Saddle River, NJ: Prentice-Hall)

  • J. R. JENSEN
  • 2000
2 Excerpts

Remote sensing of urban/suburban infrastructure and socio-economic attributes

  • J. R. JENSEN, D. C. COWEN
  • Photogrammetric Engineering and Remote Sensing,
  • 1999
1 Excerpt

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