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  Street-Level Imagery and Deep Learning for Characterization of Exposed Buildings

Aravena Pelizari, P., Geiß, C., Schoepfer, E., Riedlinger, T., Aguirre, P., Santa María, H., Merino Peña, Y., Gomez- Zapata, J. C., Pittore, M., Taubenböck, H. (2021): Street-Level Imagery and Deep Learning for Characterization of Exposed Buildings - Abstracts, EGU General Assembly 2021 (Online 2021).
https://doi.org/10.5194/egusphere-egu21-9903

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Item Permalink: https://gfzpublic.gfz.de/pubman/item/item_5005981 Version Permalink: https://gfzpublic.gfz.de/pubman/item/item_5005981_3
Genre: Conference Paper

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 Creators:
Aravena Pelizari, P.1, Author
Geiß, C.1, Author
Schoepfer, E.1, Author
Riedlinger, T.1, Author
Aguirre, P.1, Author
Santa María, H.1, Author
Merino Peña, Y.1, Author
Gomez- Zapata, Juan Camilo2, Author                 
Pittore, M.1, Author
Taubenböck, H.1, Author
Affiliations:
1External Organizations, ou_persistent22              
22.6 Seismic Hazard and Risk Dynamics, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146032              

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Language(s): eng - English
 Dates: 2021-03-052021
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.5194/egusphere-egu21-9903
GFZPOF: p4 T3 Restless Earth
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Title: EGU General Assembly 2021
Place of Event: Online
Start-/End Date: 2021-04-19 - 2021-04-30

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Title: Abstracts
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: -