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Feature subspaces selection via one-class SVM: Application to textured image segmentation.

, , and . IPTA, page 21-25. IEEE, (2010)

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Hyperspectral Remote Sensing Image Classification Based on Rotation Forest., , , and . IEEE Geosci. Remote Sensing Lett., 11 (1): 239-243 (2014)Sélection aléatoire d'espaces de représentation pour la décision binaire en environnement non-stationnaire: application à la segmentation d'images texturées., , and . Les Relations Spatiales, volume E-14 of RNTI, Cépaduès-Éditions, (2008)A Benchmark for 3D Mesh Watermarking., , , , and . Shape Modeling International, page 231-235. IEEE Computer Society, (2010)MRF-Based Multiple Classifier System for Hyperspectral Remote Sensing Image Classification., , and . MCS, volume 7872 of Lecture Notes in Computer Science, page 343-351. Springer, (2013)Random Subspace Ensembles for Hyperspectral Image Classification With Extended Morphological Attribute Profiles, , , , and . IEEE Transactions on Geoscience and Remote Sensing, 53 (9): 4768-4786 (2015)Utilizing Deep Object Detector for Video Surveillance Indexing and Retrieval., , , and . MMM (2), volume 11296 of Lecture Notes in Computer Science, page 506-518. Springer, (2019)Hyperspectral remote sensing image classification based on the integration of support vector machine and random forest., , , and . IGARSS, page 174-177. IEEE, (2012)Feature subspaces selection via one-class SVM: Application to textured image segmentation., , and . IPTA, page 21-25. IEEE, (2010)Dynamic Decision Method Based on Contextual Selection of Representation Subspaces., , , and . ICMLA, page 567-572. IEEE Computer Society, (2010)Rotation-Based Support Vector Machine Ensemble in Classification of Hyperspectral Data With Limited Training Samples., , , and . IEEE Trans. Geosci. Remote. Sens., 54 (3): 1519-1531 (2016)