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Artificial Neural Network Approach for Land Cover Classification of Fused Hyperspectral and Lidar Data.

, , and . AIAI, volume 412 of IFIP Advances in Information and Communication Technology, page 255-261. Springer, (2013)

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Simultaneously sparse and low-rank abundance matrix estimation for hyperspectral image unmixing., , , and . CoRR, (2015)Online Bayesian low-rank subspace learning from partial observations., , , and . EUSIPCO, page 2526-2530. IEEE, (2015)Artificial Neural Network Approach for Land Cover Classification of Fused Hyperspectral and Lidar Data., , and . AIAI, volume 412 of IFIP Advances in Information and Communication Technology, page 255-261. Springer, (2013)Simultaneously Sparse and Low-Rank Abundance Matrix Estimation for Hyperspectral Image Unmixing., , , and . IEEE Trans. Geoscience and Remote Sensing, 54 (8): 4775-4789 (2016)Alternating Iteratively Reweighted Least Squares Minimization for Low-Rank Matrix Factorization., , and . IEEE Trans. Signal Processing, 67 (2): 490-503 (2019)A Projected Newton-type Algorithm for Nonnegative Matrix Factorization with Model Order Selection., , and . ICASSP, page 3497-3501. IEEE, (2019)Implicit Bias of Projected Subgradient Method Gives Provable Robust Recovery of Subspaces of Unknown Codimension., , and . CoRR, (2022)Low-rank and Sparse NMF for Joint Endmembers' Number Estimation and Blind Unmixing of Hyperspectral Images., , and . CoRR, (2017)Robust PCA via Alternating Iteratively Reweighted Low-Rank Matrix Factorization., , and . ICIP, page 3383-3387. IEEE, (2018)A Computationally Efficient Tensor Completion Algorithm., , , and . IEEE Signal Process. Lett., 25 (8): 1266-1270 (2018)