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Decision fusion for hyperspectral image classification based on minimum-distance classifiers in thewavelet domain.

, , , , and . ChinaSIP, page 162-165. IEEE, (2014)

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Transformation learning based domain adaptation for robust classification of disparate hyperspectral data., and . IGARSS, page 3640-3643. IEEE, (2017)Person Re-identification with Hyperspectral Multi-Camera Systems - A Pilot Study., , , and . CoRR, (2016)Locality Preserving Genetic Algorithms for Spatial-Spectral Hyperspectral Image Classification., , , and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 6 (3): 1688-1697 (2013)Superpixel-Based Active Learning and Online Feature Importance Learning for Hyperspectral Image Analysis., , , , and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 10 (1): 347-359 (2017)Compressive data fusion for multi-sensor image analysis., , and . ICIP, page 5032-5036. IEEE, (2014)High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton., , , and . EMBC, page 5606-5609. IEEE, (2013)Rotation invariance through structured sparsity for robust hyperspectral image classification., , , and . ICASSP, page 6205-6209. IEEE, (2017)Robust sub-pixel hyperspectral classification via locality preserving feature extraction and a dirichlet process mixture model., , and . WHISPERS, page 1-4. IEEE, (2013)Region growing based joint sparsity model for hyperspectral image analysis., and . WHISPERS, page 1-4. IEEE, (2013)Utilization of Local and Global Hyperspectral Features via Wavelet Packets and Multiclassifiers for Robust Target Recognition., , , and . IGARSS (3), page 825-828. IEEE, (2009)