Abstract
The traditional approaches of classification are always unfavorable in the description of information distribution. This paper describes the BP neural network approach and the Kohonen neural network approach to the classification of remote sensing images. Two algorithms have their own traits and can be good used in the classification. A qualitative comparison demonstrates that both original images and the classified maps are visually well matched. A further quantitative analysis indicates that the accuracy of BP algorithm is better than the result of the Kohonen neural network
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References
Chungen, Y., Lasse, R., Zhongyang, L.: Methods to Improve Prediction Performance of ANN Models. Simulation Modelling Practice and Theory 11, 211–222 (2003)
Kimes, D.S., Nelson, R.F.: Attributes of Networks for Extracting Continuous Vegetation Variables. Int. J. Remote Sensing 19, 2639–2663 (1998)
Rangsanseri, Y., Thitimajshima, P., Promcharoen, S.: A Study of Neural Network Cassification of JERS-1/OPS Iages. In: 19th Asian Conference on Remote Sensing (1998)
Mannan, B., Roy, J., Ray, A.K.: Fuzzy ARTMAP Supervised Classification of Multi- Spectral Remotely-Sensed Images. Int. J. Remote Sensing 19, 767–774 (1998)
Rongyi, Y., Shenchu, X.: Analysis on Design of Kohonen Network System Based on Classification of Complex Signals. Photonics and Technology 8, BeiJing (2002)
Hu, Y., Wu, G.: Modified RLS Training Algorithm for Multi-Layer Feed-Forward Neural Networks. System Engineering and Electronics Technology 22, 77–80 (2000)
Aoyama, T., Hanxi, Z., Yoshihara, L.: Forecasting of the Chaos by Iterations Including Multi-Layer Neural Network. In: Proceedings of the International Joint Conference on Neural Networks, pp. 467–471 (2000)
Fiset, R., Cavayas, F.: Automatic Comparison of a Topographic Map with Remotely Sensed Images in a Map Updating Perspective: The Road Network Case. Int. J. Remote Sensing 18, 991–1006 (1997)
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© 2004 Springer-Verlag Berlin Heidelberg
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Chen, Y., Wan, Y., Gong, J., Chen, J. (2004). Comparison with Two Classification Algorithms of Remote Sensing Image Based on Neural Network. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks – ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28647-9_149
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DOI: https://doi.org/10.1007/978-3-540-28647-9_149
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22841-7
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