Research on Image Classification Algorithm Based on Artificial Immune Learning

Abstract : On the basis of analyzing immune learning mechanism, by modeling for image classification, we can solve the problem of remote sensing image classification by using the basic principles of the use of immune learning. We have realized a classification algorithm with a function of the immune learning. Classification algorithm divides each major category into a number of small categories and the antigen population evolutionary process of each category is considered separately, therefore the convergence time is greatly decreased. When classifying, we use a variety of different ways to discriminate and introduce artificial priori knowledge to improve the classification accuracy. The results show that the algorithm can be well applied in remote sensing image classification.
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Communication dans un congrès
Daoliang Li; Yande Liu; Yingyi Chen. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. Springer, IFIP Advances in Information and Communication Technology, AICT-346 (Part III), pp.403-412, 2011, Computer and Computing Technologies in Agriculture IV. 〈10.1007/978-3-642-18354-6_48〉
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Soumis le : lundi 17 juillet 2017 - 17:00:54
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Chengming Zhang, Yong Liang, Shujing Wan, Jinping Sun, Dalei Zhang. Research on Image Classification Algorithm Based on Artificial Immune Learning. Daoliang Li; Yande Liu; Yingyi Chen. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. Springer, IFIP Advances in Information and Communication Technology, AICT-346 (Part III), pp.403-412, 2011, Computer and Computing Technologies in Agriculture IV. 〈10.1007/978-3-642-18354-6_48〉. 〈hal-01563491〉

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