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Spatial-Spectral Feature Extraction With Local Covariance Matrix From Hyperspectral Images Through Hybrid Parallelization., , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2023)Convex formulation for hyperspectral image classification with superpixels., , , , and . IGARSS, page 3294-3297. IEEE, (2016)Parallel techniques for information extraction from hyperspectral imagery using heterogeneous networks of workstations.. J. Parallel Distributed Comput., 68 (1): 93-111 (2008)A Signal Processing Perspective on Hyperspectral Unmixing: Insights from Remote Sensing., , , , , , , and . IEEE Signal Process. Mag., 31 (1): 67-81 (2014)Minimum volume simplicial enclosure for spectral unmixing of remotely sensed hyperspectral data., , , and . IGARSS, page 193-196. IEEE, (2010)Self-Organizing Map for Hyperspectral Image Analysis., , , , , and . IWANN (2), volume 2085 of Lecture Notes in Computer Science, page 208-218. Springer, (2001)Scanning the Issue., , , , , , , , , and 3 other author(s). Proc. IEEE, 107 (12): 2306-2307 (2019)Exploiting spatial information in semi-supervised hyperspectral image segmentation., , and . WHISPERS, page 1-4. IEEE, (2010)On the architecture of a big data classification tool based on a map reduce approach for hyperspectral image analysis., , , , , , , and . IGARSS, page 1508-1511. IEEE, (2015)The Future of Imaging Spectroscopy Prospective Technologies and Applications., , , , , , , , , and 10 other author(s). IGARSS, page 2005-2009. IEEE, (2006)