Ensemble of half-space trees for hyperspectral anomaly detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s11432-021-3310-x.pdf
Reference42 articles.
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2. Chen J, Ling Z C, Qiao L, et al. Mineralogy of Chang’e-4 landing site: preliminary results of visible and near-infrared imaging spectrometer. Sci China Inf Sci, 2020, 63: 140903
3. Pu H Y, Wang B, Zhang L M. Simplex geometry-based abundance estimation algorithm for hyperspectral unmixing (in Chinese). Sci Sin Inform, 2012, 42: 1019–1033
4. Wang Q, He X, Li X. Locality and structure regularized low rank representation for hyperspectral image classification. IEEE Trans Geosci Remote Sens, 2019, 57: 911–923
5. Hou Z F, Wei L, Tao R, et al. Collaborative representation with background purification and saliency weight for hyperspectral anomaly detection. Sci China Inf Sci, 2022, 65: 112305
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