PRISMA Hyperspectral Image Segmentation with U-Net Convolutional Neural Network Using Singular Value Decomposition for Mapping Mining Areas: Preliminary Results-Reference-Cited by-同舟云学术

PRISMA Hyperspectral Image Segmentation with U-Net Convolutional Neural Network Using Singular Value Decomposition for Mapping Mining Areas: Preliminary Results

Published:2023 Issue: Volume: Page:327-340
ISSN:1860-949X
Container-title:Studies in Computational Intelligence
language:
Short-container-title:

Author:

Dosi Andrea^ORCID,Pesce Michele^ORCID,Di Nardo Anna^ORCID,Pafundi Vincenzo^ORCID,Delli Veneri Michele^ORCID,Chirico Rita^ORCID,Ammirati Lorenzo^ORCID,Mondillo Nicola^ORCID,Longo Giuseppe^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-25755-1_22

Reference20 articles.

1. Ammirati, L., Chirico, R., Di Martire, D., Mondillo, N.: Application of multispectral remote sensing for mapping flood-affected zones in the brumadinho mining district (minas gerais, brasil). Remote Sens. 14(6) (2022). https://doi.org/10.3390/rs14061501, https://www.mdpi.com/2072-4292/14/6/1501

2. Boni, M., Balassone, G., Iannace, A.: Base metal ores in the lower paleozoic of southwestern sardinia. In: Carbonate-Hosted Lead-Zinc Deposits: 75th Anniversary Volume. Society of Economic Geologists (Jan 1996). https://doi.org/10.5382/SP.04.03

3. Chemale, F., Rosière, C.A., Endo, I.: The tectonic evolution of the quadrilátero ferrífero, minas gerais, brazil. Precambr. Res. 65(1), 25–54 (1994). https://doi.org/10.1016/0301-9268(94)90098-1, https://www.sciencedirect.com/science/article/pii/0301926894900981

4. Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs. IEEE Trans. Pattern Anal. Mach. Intell. 40(4), 834–848 (2017)

5. Cidu, R., Fanfani, L.: Overview of the environmental geochemistry of mining districts in southwestern sardinia. Italy. Geochem. Explor. Environ. Anal. 2, 243–251 (2002). https://doi.org/10.1144/1467-787302-028