Faint spatial object classifier construction based on data mining technology

Xin Lou; Yang Zhao; Yurong Liao; Yong-ming Nie

doi:10.1117/12.2256285

7 November 2016 Faint spatial object classifier construction based on data mining technology

Xin Lou, Yang Zhao, Yurong Liao, Yong-ming Nie

Proceedings Volume 10141, Selected Papers of the Chinese Society for Optical Engineering Conferences held July 2016; 101411K (2016) https://doi.org/10.1117/12.2256285
Event: Selected Proceedings of the Chinese Society for Optical Engineering Conferences held July 2016, 2016, Changchun, China

Abstract

Data mining can effectively obtain the faint spatial object’s patterns and characteristics, the universal relations and other implicated data characteristics, the key of which is classifier construction. Faint spatial object classifier construction with spatial data mining technology for faint spatial target detection is proposed based on theoretical analysis of design procedures and guidelines in detail. For the one-sidedness weakness during dealing with the fuzziness and randomness using this method, cloud modal classifier is proposed. Simulating analyzing results indicate that this method can realize classification quickly through feature combination and effectively resolve the one-sidedness weakness problem.

Citation Download Citation

Xin Lou, Yang Zhao, Yurong Liao, and Yong-ming Nie "Faint spatial object classifier construction based on data mining technology", Proc. SPIE 10141, Selected Papers of the Chinese Society for Optical Engineering Conferences held July 2016, 101411K (7 November 2016); https://doi.org/10.1117/12.2256285

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