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Matrix Cofactorization for Joint Representation Learning and Supervised Classification - Application to Hyperspectral Image Analysis.

, , , , и . CoRR, (2019)

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Benchmarking classification of earth-observation data: From learning explicit features to convolutional networks., , , , , , , и . IGARSS, стр. 4173-4176. IEEE, (2015)From representation learning to thematic classification - Application to hierarchical analysis of hyperspectral images. (De l'apprentissage de représentation à la classification thématique - Application à l'analyse hiérarchique d'images hyperspectrales).. National Polytechnic Institute of Toulouse, France, (2019)Matrix cofactorization for joint representation learning and supervised classification - Application to hyperspectral image analysis., , , , и . Neurocomputing, (2020)Matrix Cofactorization for Joint Spatial-Spectral Unmixing of Hyperspectral Images., , , и . IEEE Trans. Geosci. Remote. Sens., 58 (7): 4915-4927 (2020)Matrix cofactorization for joint spatial-spectral unmixing of hyperspectral images., , , и . CoRR, (2019)Matrix Cofactorization for Joint Unmixing and Classification of Hyperspectral Images., , , , и . EUSIPCO, стр. 1-5. IEEE, (2019)Matrix Cofactorization for Joint Representation Learning and Supervised Classification - Application to Hyperspectral Image Analysis., , , , и . CoRR, (2019)Processing of Extremely High-Resolution LiDAR and RGB Data: Outcome of the 2015 IEEE GRSS Data Fusion Contest-Part A: 2-D Contest., , , , , , , , , и 5 other автор(ы). IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 9 (12): 5547-5559 (2016)