RETRACTED ARTICLE: Sensor-based mountain landslide sensitivity and logistics supply chain management optimization
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences,General Environmental Science
Link
https://link.springer.com/content/pdf/10.1007/s12517-021-07995-3.pdf
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2. Acosta I, Khodadadzadeh M, Tusa L, Ghamisi P, Gloaguen R (2019) A machine learning framework for drill-core mineral mapping using hyperspectral and high-resolution mineralogical data fusion. IEEE J Sel Top Appl Earth Obser Remote Sens 99:1–14. https://doi.org/10.1109/JSTARS.2019.2924292
3. Ball JE, Anderson DT, Chan CS (2017) Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community. J Appl Remote Sens 11:11–54. https://doi.org/10.1117/1.JRS.11.042609
4. Chen YS, Lin ZH, Zhao X, Wang G, Gu YF (2014) Deep learning based classification of hyperspectral data. IEEE J Sel Top Appl Earth Obs Remote Sens 7(6):2094–2107. https://doi.org/10.1109/JSTARS.2014.2329330
5. Chen Y, Zhao X, Jia X (2015) Spectral–spatial classification of hyperspectral data based on deep belief network. IEEE J Sel Topics Appl Earth Obs Remote Sens 8(6):2381–2392. https://doi.org/10.1109/JSTARS.2015.2388577
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1. Optimization of Logistics Industry Organization Management System in Digital Intelligence Era;Lecture Notes in Electrical Engineering;2023
2. Retraction Note: Sensor-based mountain landslide sensitivity and logistics supply chain management optimization;Arabian Journal of Geosciences;2021-12
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