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Spatial-spectral endmember extraction from hyperspectral imagery using multi-band morphology and volume optimization.

, , and . ICIP, page 3721-3724. IEEE, (2009)

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Minimum volume simplicial enclosure for spectral unmixing of remotely sensed hyperspectral data., , , and . IGARSS, page 193-196. IEEE, (2010)Spatial-spectral endmember extraction from hyperspectral imagery using multi-band morphology and volume optimization., , and . ICIP, page 3721-3724. IEEE, (2009)Endmember Extraction from Hyperspectral Imagery using a Parallel Ensemble Approach with Consensus Analysis., , , , , , and . IGARSS (5), page 88-91. IEEE, (2009)Fast dimensionality reduction and classification of hyperspectral images with extreme learning machines., , , and . J. Real-Time Image Processing, 15 (3): 439-462 (2018)An Investigation on Self-Normalized Deep Neural Networks for Hyperspectral Image Classification., , , and . IGARSS, page 3607-3610. IEEE, (2018)A new method for target detection in hyperspectral imagery based on extended morphological profiles., , , and . IGARSS, page 3772-3774. IEEE, (2003)A New 3D Convolution Network for Hyperspectral Unmixing., , , , , , , , and . IGARSS, page 1620-1623. IEEE, (2022)High-performance computing in remotely sensed hyperspectral imaging: the Pixel Purity Index algorithm as a case study., , and . IPDPS, IEEE, (2006)Parallel CBIR System for Efficient Hyperspectral Image Retrieval from Heterogeneous Networks of Workstations., , , and . SYNASC, page 285-291. IEEE Computer Society, (2007)On the optimization of memory access to increase the performance of spatial preprocessing techniques on graphics processing units., , , , and . IGARSS, page 6541-6544. IEEE, (2016)