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Proceedings Paper

Fuzzy spatial objects modeling from image based on fuzzy neural network
Author(s): Zhongyuan Wang; Qingwen Qi; Zongyi He; Ping Yang
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Paper Abstract

Traditional modeling methods on spatial objects are not eligible to deal well with the fuzzy features that acquired from image, some research need to be carried out on the fuzzy spatial objects modeling. With the deep investigation on the spatial objects model of GIS and the representation of natural geographical feature, fuzzy spatial objects have been proposed by researchers. Referring to the characteristics of the representation of fuzzy spatial objects, a generation method of fuzzy spatial objects based on fuzzy Neural Networks is going to be demonstrated by the authors in this paper. By combining the fuzzy technique and neural networks, utilizing the learning ability to enhance the fuzzy membership function and fuzzy rules, the system will be self-Adaptive. By comparing with the traditional fuzzy objects generation, the method in this paper improves the accuracy of results according to the experiments in this paper.

Paper Details

Date Published: 29 December 2008
PDF: 6 pages
Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853G (29 December 2008); doi: 10.1117/12.815920
Show Author Affiliations
Zhongyuan Wang, Wuhan Univ. (China)
Institute of Geographic Sciences and Natural Resources Research (China)
Qingwen Qi, Institute of Geographic Sciences and Natural Resources Research (China)
Zongyi He, Wuhan Univ. (China)
Ping Yang, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 7285:
International Conference on Earth Observation Data Processing and Analysis (ICEODPA)
Deren Li; Jianya Gong; Huayi Wu, Editor(s)

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