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Fast implementation of kernel simplex volume analysis based on modified Cholesky factorization for endmember extraction.

, , , and . Frontiers Inf. Technol. Electron. Eng., 17 (3): 250-257 (2016)

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Fast implementation of kernel simplex volume analysis based on modified Cholesky factorization for endmember extraction., , , and . Frontiers Inf. Technol. Electron. Eng., 17 (3): 250-257 (2016)基于逐像素递归处理的高光谱实时亚像元目标检测 (Real-time Sub-pixel Object Detection for Hyperspectral Image Based on Pixel-by-pixel Processing)., , and . 计算机科学, 45 (6): 259-264 (2018)Kernel-OPBS Algorithm: A Nonlinear Feature Selection Method for Hyperspectral Imagery., , , , and . IEEE Geosci. Remote. Sens. Lett., 17 (3): 464-468 (2020)Normalizing Flow-Based Probability Distribution Representation Detector for Hyperspectral Anomaly Detection., , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2022)Unsupervised Feature Learning by Autoencoder and Prototypical Contrastive Learning for Hyperspectral Classification., , and . CoRR, (2020)Recursive Local Summation of RX Detection for Hyperspectral Image Using Sliding Windows., , , and . Remote. Sens., 10 (1): 103 (2018)A novel Bayesian lasso model based on spatial-correlated sparsity for semisupervised hyperspectral unmixing., , , and . IGARSS, page 5434-5437. IEEE, (2017)Novel Design of Decision-Tree-Based Support Vector Machines Multi-class Classifier., , and . ICIC (2), volume 4682 of Lecture Notes in Computer Science, page 871-880. Springer, (2007)ContrastNet: Unsupervised feature learning by autoencoder and prototypical contrastive learning for hyperspectral imagery classification., , , , , and . Neurocomputing, (2021)Exploring the Intrinsic Probability Distribution for Hyperspectral Anomaly Detection., , , and . CoRR, (2021)