Multi-view adaptive disagreement based active learning for hyperspectral image classification

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn , Issue , 2010, Pages 1374-1377

  Di, Wei ^a   Crawford, Melba M ^a  

^a PURDUE UNIVERSITY   (United States)

Author keywords

Active learning; Classification; Hyperspectral image; Multi view learning

Indexed keywords

CLASSIFICATION (OF INFORMATION); HYPERSPECTRAL IMAGING; IMAGE CLASSIFICATION; REMOTE SENSING; SPECTROSCOPY;

ACTIVE LEARNING; ACTIVE LEARNING METHODS; CLASSIFICATION CONFIDENCE; HYPERSPECTRAL DATA; HYPERSPECTRAL IMAGE DATAS; MULTI-VIEW ADAPTIVE; MULTI-VIEW LEARNING; SUPERVISED CLASSIFICATION;

LEARNING SYSTEMS;

EID: 78650907095     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2010.5650990     Document Type: Conference Paper

References (11)

1. S. Rajan, J. Ghosh, and M. M. Crawford, "An active learning approach to hyperspectral data classification," IEEE Trans. Geosci. Remote Sens., vol. 46, no. 4, pp. 1231-1242, Apr. 2008. (Pubitemid 351459470)
2. D. Tuia, F. Ratle, F. Pacifici, M. F. Kanevski, and W. J. Emery, "Active Learning Methods for Remote Sensing Image Classification", IEEE Trans. Geosci. Remote Sens., vol. 47, no. 7, pp. 2218-2232, July. 2009.
3. G. Jun, J. Ghosh, "An Efficient Active Learning Algorithm with Knowledge Transfer for Hyperspectral Data Analysis", IEEE Int. Symp. Geosci. and Remote Sens., vol. 1, pp:52-55, Jul. 2008.
4. Burr Settles. "Active Learning Literature Survey". Computer Sciences Technical Report 1648, Wisconsin-Madison, 2009.
5. I. Muslea, S. Minton, and C. A. Knoblock. "Active Learning with Multiple Views". Journal of Artifical Intelligence Research, vol. 27, pp 203-233, 2006
6. S. Tong, D. Koller, "Support vector machine active learning with applications to text classification," The Journal of Machine Learning Research archive, vol.2, pp.45-66, March 2002.
7. I. Muslea, S. Minton and C. Knoblock, "Active + semi-supervised learning=robust multi-view learning", Proc. of Int. Conf. Machine Learning, pp.435-442, Jul. 2002.
8. S. Abney, "Bootstrapping," In Proc. of 40th Meeting of the Association for Computational Linguistics, pp. 360-367, 2002.
9. B. Leskes, "The Value of Agreement a new boosting algorithm," Master Thesis, University of Amsterdam, 2002.
10. F. Olsson, "A literature survey of active machine learning in the context of natural language processing," Technical Report, Swedish Institute of Computer Science, April 17, 2009.
11. 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