Knowledge-based semi-supervised satellite image classification

2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings

Volumn , Issue , 2007, Pages

  Al Momani, Bilal ^a   Morrow, Philip ^a   McClean, Sally ^a  

^a UNIVERSITY OF ULSTER   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

FORMAL LOGIC; GEODETIC SATELLITES; GEOMORPHOLOGY; IMAGE ANALYSIS; IMAGE CLASSIFICATION; KNOWLEDGE BASED SYSTEMS; SATELLITE IMAGERY; SIGNAL PROCESSING;

INTERNATIONAL SYMPOSIUM; LAND COVERS;

CLASSIFICATION (OF INFORMATION);

EID: 51549121107     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISSPA.2007.4555340     Document Type: Conference Paper

References (16)

1. R.R. Vatsavai, S. Shekhar, and T.E Burk, "A Semi-Supervised Learning Method for Remote Sensing Data Mining," in Proc. ICTAI, pp. 207 - 211, 2005.
2. Q. Tian, J. Yu, Q. Xue, and N. Sebe, "A new analysis of the value of unlabelled data in semi-supervised learning for image retrieval," ICME, vol. 2, pp. 1019-1022, June. 2004.
3. M. Benkhalifa, A. Bensaid, and A. Mouradi, "Text categorization using the semi-supervised fuzzy c-means algorithm," NAFIPS, pp. 561-565, June 1999.
4. G. Huimin, D. Xutao, D. Bastola, and H. Ali, "On clustering biological data using unsupervised and semi-supervised message passing," BIBE, pp. 294 - 298, 2005.
5. L. Gomez-Chova, J. Calpe, G. Camps-Valls, J.D. Martin, E. Soria, J. Vila, L. Alonso-Chorda, and J. Moreno, "Semi-supervised classification method for hyperspectral remote sensing images," Geosciences and Remote Sensing Symposium in Proc. IEEE-IGARSS, vol. 3, pp. 1776-1778, July 2003.
6. A.P. Dempster, N. M. Laird, and D.B. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," Royal Statistical Soc. B, vol. 39, pp. 1-39, 1977.
7. F.G. Cozman, and I. Cohen, "Unlabelled Data Can Degrade Classification Performance of Generative Classifiers," in Proc. of 15th International Artificial Intelligence Conference, pp. 327-331, 2002.
8. A.P. Dempster, "A Generalisation of Bayesian Inference," J. of the Royal Statistical Society B, vol. 30, pp. 205-247, 1968.
9. J.W. Guan and D.A. Bell, Evidence Theory and its Applications, Elsevier Science Inc., New York, 1991.
10. S.I. McClean, and B.W. Scotney, "Using Evidence Theory for the Integration of Distributed Databases," Int. Journal of Intelligent Systems, vol. 12, pp. 763-776, 1997.
11. S. Le H'egarat-Mascle, D. Richard, and C. Ottl'e, "Multi-scale data fusion using Dempster-Shafer evidence theory," ICAE, vol. 10, pp. 9-22, 2003.
12. M.R. Ahmadzadeh, M. Petrou, "Use of Dempster-Shafer theory to combine classifiers which use different class boundaries," Pattern Anal Applic, vol. 6, pp. 41-46, 2003.
13. R.R. Yager, K.J. Engemann, and D.P. Filev, "On the Concept of Immediate Probabilities," Int. Journal of Intelligent Systems, vol. 10, pp. 373-397, 1995.
14. G.J. McLachlan, The EM Algorithm and Extensions, John Wiley & Sons Inc, 1997.
15. The US Geological Survey website- http://seamless.usgs.gov. Cited 10 Dec 2006.
16. R.G. Congalton, "Accuracy assessment and validation of remotely sensed and other spatial information," Int. Journal of Wildland Fire, vol. 10, pp. 321-328, 2001.