A classifier ensemble based on fusion of support vector machines for classifying hyperspectral data
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Johannes R. Sveinsson | Jon Atli Benediktsson | Jocelyn Chanussot | Mathieu Fauvel | Xavier Ceamanos | Björn Waske | J. R. Sveinsson | J. Benediktsson | J. Chanussot | X. Ceamanos | M. Fauvel | J. Sveinsson | B. Waske
[1] David A. Landgrebe,et al. Covariance estimation with limited training samples , 1999, IEEE Trans. Geosci. Remote. Sens..
[2] Anthony Widjaja,et al. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2003, IEEE Transactions on Neural Networks.
[3] Lawrence O. Hall,et al. A Comparison of Decision Tree Ensemble Creation Techniques , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[4] G. F. Hughes,et al. On the mean accuracy of statistical pattern recognizers , 1968, IEEE Trans. Inf. Theory.
[5] Fabio Roli,et al. Methods for Designing Multiple Classifier Systems , 2001, Multiple Classifier Systems.
[6] Jon Atli Benediktsson,et al. Proceedings of the 8th International Workshop on Multiple Classifier Systems , 2009, International Workshop on Multiple Classifier Systems.
[7] Benjamin Koetz,et al. Multi-source land cover classification for forest fire management based on imaging spectrometry and LiDAR data , 2008 .
[8] Paul M. Mather,et al. Some issues in the classification of DAIS hyperspectral data , 2006 .
[9] Lorenzo Bruzzone,et al. Kernel-based methods for hyperspectral image classification , 2005, IEEE Transactions on Geoscience and Remote Sensing.
[10] Joydeep Ghosh,et al. Investigation of the random forest framework for classification of hyperspectral data , 2005, IEEE Transactions on Geoscience and Remote Sensing.
[11] Lorenzo Bruzzone,et al. Classification of hyperspectral remote sensing images with support vector machines , 2004, IEEE Transactions on Geoscience and Remote Sensing.
[12] Jon Atli Benediktsson,et al. Classification of multisource and hyperspectral data based on decision fusion , 1999, IEEE Trans. Geosci. Remote. Sens..
[13] Lorenzo Bruzzone,et al. Fusion of Hyperspectral and LIDAR Remote Sensing Data for Classification of Complex Forest Areas , 2008, IEEE Transactions on Geoscience and Remote Sensing.
[14] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[15] Oleksandr Makeyev,et al. Neural network with ensembles , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).
[16] Jon Atli Benediktsson,et al. Fusion of Support Vector Machines for Classification of Multisensor Data , 2007, IEEE Transactions on Geoscience and Remote Sensing.
[17] Jon Atli Benediktsson,et al. Multiple Classifier Systems in Remote Sensing: From Basics to Recent Developments , 2007, MCS.
[18] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[19] David W. Opitz,et al. Actively Searching for an E(cid:11)ective Neural-Network Ensemble , 1996 .
[20] Björn Waske,et al. Classifying Multilevel Imagery From SAR and Optical Sensors by Decision Fusion , 2008, IEEE Transactions on Geoscience and Remote Sensing.
[21] R. Schapire. The Strength of Weak Learnability , 1990, Machine Learning.
[22] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[23] Anders Krogh,et al. Neural Network Ensembles, Cross Validation, and Active Learning , 1994, NIPS.
[24] Paul M. Mather,et al. Assessment of the effectiveness of support vector machines for hyperspectral data , 2004, Future Gener. Comput. Syst..
[25] Josef Kittler,et al. Combining classifiers: A theoretical framework , 1998, Pattern Analysis and Applications.
[26] Johannes R. Sveinsson,et al. Multiple classifiers applied to multisource remote sensing data , 2002, IEEE Trans. Geosci. Remote. Sens..