Comparison of multisource data support vector Machine classification for mapping of forest cover
暂无分享,去创建一个
[1] A. Jakomulska,et al. Variogram-Derived Measures of Textural Image Classification , 2001 .
[2] Vladimir Vapnik,et al. An overview of statistical learning theory , 1999, IEEE Trans. Neural Networks.
[3] J. Carr,et al. Semivariogram textural classification of JERS-1 (Fuyo-1) SAR data obtained over a flooded area of the Amazon rainforest , 1998 .
[4] Robert M. Haralick,et al. Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..
[5] Paul M. Mather,et al. Support vector machines for classification in remote sensing , 2005 .
[6] B. Turner,et al. Performance of a neural network: mapping forests using GIS and remotely sensed data , 1997 .
[7] L. S. Davis,et al. An assessment of support vector machines for land cover classi(cid:142) cation , 2002 .
[8] Mario Chica-Olmo,et al. Computing geostatistical image texture for remotely sensed data classification , 2000 .
[9] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[10] Lingmin He,et al. Multiclass SVM based land cover classification with multisource data , 2005, 2005 International Conference on Machine Learning and Cybernetics.
[11] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[12] Richard Gloaguen,et al. Geostatistical Texture Classification of Tropical Rainforest in Indonesia , 2008 .
[13] M. Keller,et al. CANOPY DAMAGE AND RECOVERY AFTER SELECTIVE LOGGING IN AMAZONIA: FIELD AND SATELLITE STUDIES , 2004 .