Modified Genetic Algorithm (MGA) based feature selection with Mean Weighted Least Squares Twin Support Vector Machine (MW-LSTSVM) approach for vegetation classification-Reference-Cited by-同舟云学术

Modified Genetic Algorithm (MGA) based feature selection with Mean Weighted Least Squares Twin Support Vector Machine (MW-LSTSVM) approach for vegetation classification

Published:2018-02-17 Issue:S6 Volume:22 Page:13569-13581
ISSN:1386-7857
Container-title:Cluster Computing
language:en
Short-container-title:Cluster Comput

Author:

Priya V. Shenbaga,Ramyachitra D.

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Software

Link

http://link.springer.com/article/10.1007/s10586-018-2003-8/fulltext.html

Reference38 articles.

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3. Czaplewski, R.L., Patterson, P.L.: Classification accuracy for stratification with remotely sensed data. For. Sci. 49(3), 402–408 (2003)

4. Ehlers, M., Gahler, M., Janowsky, R.: Automated analysis of ultra high-resolution remote sensing data for biotope type mapping: new possibilities and challenges. ISPRS J. Photogramm. Remote Sens. 57(5–6), 315–326 (2003)

5. Benediktsson, J.A., Pesaresi, M., Arnason, K.: Classification and feature extraction for remote sensing images from urban areas based on morphological transformations. IEEE Trans. Geosci. Remote Sens. 41(9), 1940–1949 (2003)

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