Please use this identifier to cite or link to this item:
https://open.uns.ac.rs/handle/123456789/16010
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lindblad J. | en |
dc.contributor.author | Lukić T. | en |
dc.contributor.author | Sladoje N. | en |
dc.date.accessioned | 2020-03-03T15:02:14Z | - |
dc.date.available | 2020-03-03T15:02:14Z | - |
dc.date.issued | 2007-12-01 | en |
dc.identifier.isbn | 9789531841160 | en |
dc.identifier.uri | https://open.uns.ac.rs/handle/123456789/16010 | - |
dc.description.abstract | We introduce the use of DC programming, in combination with convex-concave regularization, as a deterministic approach for solving the optimization problem imposed by defuzzification by feature distance minimization. We provide a DC based algorithm for finding a solution to the defuzzification problem by expressing the objective function as a difference of two convex functions and iteratively solving a family of DC programs. We compare the performance with the previously recommended method, simulated annealing, on a number of test images. Encouraging results, together with several advantages of the DC based method, approve use of this approach, and motivate its further exploration. | en |
dc.relation.ispartof | ISPA 2007 - Proceedings of the 5th International Symposium on Image and Signal Processing and Analysis | en |
dc.title | Defuzzification by feature distance minimization based on DC programming | en |
dc.type | Conference Paper | en |
dc.identifier.doi | 10.1109/ISPA.2007.4383722 | en |
dc.identifier.scopus | 2-s2.0-47949101867 | en |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/47949101867 | en |
dc.relation.lastpage | 378 | en |
dc.relation.firstpage | 373 | en |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
Appears in Collections: | FTN Publikacije/Publications |
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