| Technology and Methodology |
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A COMPARATIVE STUDY OF PROBABILISTIC NEURAL NETWORK AND BP NETWORKS FOR REMOTE SENSING IMAGE CLASSIFICATION |
| LI Chao-feng1, YANG Mao-long2, XU Lei1, YANG Meng-zhao1 |
1. School of Information Technology, Southern Yangtze University, Wuxi 214036, China;
2. Department of Space Reconnaissance, University of Foreign Relations, PLA, Nanjing 210039, China |
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Abstract This paper has analyzed the basic theory and algorithm of the probabilistic neural network, and established the remote sensing image classification model based on the probabilistic neural network. Examples show that the probabilistic neural network model outperforms the improved back-propagation neural network model in classification precision and is close to the latter in time consumption. It proves to be an efficient image classification method.
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Issue Date: 02 August 2011
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2004,
Vol. 16
