A comparison of differential evolution and Harmony Search methods for SVM model selection in hyperspectral image classification

Oguzhan Ceylan; Gulsen Taskin

doi:10.1109/IGARSS.2016.7729120

A comparison of differential evolution and Harmony Search methods for SVM model selection in hyperspectral image classification

Oguzhan Ceylan, Gulsen Taskin

Disaster Management Institute

Altinbas University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

Support vector machines is a very popular method in classification of hyperspectral images due to their good generalization capability even with a limited number of training datasets. However, the performance of SVM strongly depends on selection of kernel parameters when RBF kernel is used. In order to achieve a high classification performance, the kernel parameters, that are the value of regularization term and kernel width, should optimally be chosen. In this work, the use of recently developed evolutionary optimization methods, harmony search and differential evolution methods, are investigated in the context of hyperspectral image classification for the first time in this paper. The experimental results showed that these methods provide fast and accurate results in comparison to classical grid search approach.

Original language	English
Title of host publication	2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	485-488
Number of pages	4
ISBN (Electronic)	9781509033324
DOIs	https://doi.org/10.1109/IGARSS.2016.7729120
Publication status	Published - 1 Nov 2016
Event	36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Beijing, China Duration: 10 Jul 2016 → 15 Jul 2016

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	2016-November

Conference

Conference	36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
Country/Territory	China
City	Beijing
Period	10/07/16 → 15/07/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

Differential evolution
Harmony search
Hyperspectral image classification
model selection

Access to Document

10.1109/IGARSS.2016.7729120

Cite this

Ceylan, O., & Taskin, G. (2016). A comparison of differential evolution and Harmony Search methods for SVM model selection in hyperspectral image classification. In 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings (pp. 485-488). Article 7729120 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2016-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2016.7729120

Ceylan, Oguzhan ; Taskin, Gulsen. / A comparison of differential evolution and Harmony Search methods for SVM model selection in hyperspectral image classification. 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 485-488 (International Geoscience and Remote Sensing Symposium (IGARSS)).

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abstract = "Support vector machines is a very popular method in classification of hyperspectral images due to their good generalization capability even with a limited number of training datasets. However, the performance of SVM strongly depends on selection of kernel parameters when RBF kernel is used. In order to achieve a high classification performance, the kernel parameters, that are the value of regularization term and kernel width, should optimally be chosen. In this work, the use of recently developed evolutionary optimization methods, harmony search and differential evolution methods, are investigated in the context of hyperspectral image classification for the first time in this paper. The experimental results showed that these methods provide fast and accurate results in comparison to classical grid search approach.",

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Ceylan, O & Taskin, G 2016, A comparison of differential evolution and Harmony Search methods for SVM model selection in hyperspectral image classification. in 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings., 7729120, International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2016-November, Institute of Electrical and Electronics Engineers Inc., pp. 485-488, 36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016, Beijing, China, 10/07/16. https://doi.org/10.1109/IGARSS.2016.7729120

A comparison of differential evolution and Harmony Search methods for SVM model selection in hyperspectral image classification. / Ceylan, Oguzhan; Taskin, Gulsen.
2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. p. 485-488 7729120 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2016-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Support vector machines is a very popular method in classification of hyperspectral images due to their good generalization capability even with a limited number of training datasets. However, the performance of SVM strongly depends on selection of kernel parameters when RBF kernel is used. In order to achieve a high classification performance, the kernel parameters, that are the value of regularization term and kernel width, should optimally be chosen. In this work, the use of recently developed evolutionary optimization methods, harmony search and differential evolution methods, are investigated in the context of hyperspectral image classification for the first time in this paper. The experimental results showed that these methods provide fast and accurate results in comparison to classical grid search approach.

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Ceylan O, Taskin G. A comparison of differential evolution and Harmony Search methods for SVM model selection in hyperspectral image classification. In 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2016. p. 485-488. 7729120. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS.2016.7729120

A comparison of differential evolution and Harmony Search methods for SVM model selection in hyperspectral image classification

Abstract

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Bibliographical note

Keywords

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