An automatic method for selecting the parameter of the RBF kernel function to support vector machines

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn , Issue , 2010, Pages 836-839

  Li, Cheng Hsuan ^a,b   Lin, Chin Teng ^a   Kuo, Bor Chen ^b   Chu, Hui Shan ^b  

^a NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

^b NATIONAL TAICHUNG UNIVERSITY OF EDUCATION   (Taiwan)

Author keywords

Kernel method; Optimal kernel; Support vector machine

Indexed keywords

REMOTE SENSING;

AUTOMATIC METHOD; GRID METHODS; K FOLD CROSS VALIDATIONS; KERNEL FUNCTION; KERNEL METHODS; OPTIMAL KERNELS; RBF KERNEL FUNCTION; SUPERVISED CLASSIFICATION;

SUPPORT VECTOR MACHINES;

EID: 78650912012     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2010.5649251     Document Type: Conference Paper

References (13)

1. S. T. John and C. Nello, Kernel Methods for Pattern Analysis. Cambridge, U.K.: Cambridge Univ. Press, 2004.
2. F. Melgani and L. Bruzzone, "Classification of hyperspectral remote sensing images with support vector machines," IEEE Trans. Geosci. Remote Sens., vol. 42, no. 8, pp. 1778-1790, Aug. 2004.
3. G. Camps-Valls and L. Bruzzone, "Kernel-based methods for hyperspectral image classification," IEEE Trans. Geosci. Remote Sens, vol. 43, no. 6, pp. 1351-1362, Jun. 2005.
4. G. Camps-Valls, L. Gomez-Chova, J. Munoz-Mari, J. L. Rojo-Alvarez, and M. Martinez-Ramon, "Kernel-based framework for multitemporal and multisource remote sensing data classification and change detection," IEEE Trans. Geosci. Remote Sens., vol. 46, no. 6, pp. 1822-1835, Mar. 2008.
5. G. Camps-Valls and L. Bruzzone, Kernel Methods for Remote Sensing Data Analysis. John Wiley & Sons, Ltd, 2009.
6. G. Camps-Valls, L. Gómez-Chova, J. Calpe, E. Soria, J. D. Martín, L. Alonso, and J. Moreno, "Robust support vector method for hyperspectral data classification and knowledge discovery," IEEE Trans. Geosci. Remote Sens., vol. 42, no. 7, pp. 1530-1542, Jul. 2004.
7. C.C. Chang and C.J. Lin, LIBSVM: A Library for Support Vector Machines, 2001. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm
8. H.L. Xiong, M.N.S. Swamy, M. Omair Ahmad, "Optimizing the kernel in the empirical feature space," IEEE Trans. Neural Networks 16 (2) (2005) 460-474.
9. B. Chen, H. Liu, and Z. Bao, "Optimizing the data-dependent kernel under a unified kernel optimization framework," Pattern Recognition, vol. 41, pp. 2107-2119, 2007.
10. rd edition, John Wiley & Sons, Inc., New York, NY, USA, 2008.
11. DA. Landgrebe, Signal Theory Methods in Multispectral Remote Sensing. Hoboken, NJ: Wiley, 2003.
12. J.A. Benediktsson, JA. Palmason, and J.R. Sveinsson, "Classification of hyperspectral data from urban areas based on extended morphological profiles," IEEE Trans. Geosci. Remote Sens, vol. 43, no. 3, pp. 480-491, Mar. 2005.
13. B.S. Sebastiano and M. Gabriele, "Extraction of spectral channels from hyperspectral images for classification purposes," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 2, pp. 484-495, Feb. 2007.