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Characterizing Agri-Forestry Systems in Portugal Through High-Resolution Orthophotos and Convolutional Neural Networks

AuthID
P-00X-JYW

Author(s)

Morais, TG

Domingos, T

Teixeira, RFM

Editor(es)

Neale,CMU;Maltese,A

Tipo de Documento

Proceedings Paper

Year published

2022

Publicado

in REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XXIV in Proceedings of SPIE, ISSN: 0277-786X

Volume: 12262

Conference

Conference on Remote Sensing for Agriculture, Ecosystems, and Hydrology Xxiv Part of Spie Remote Sensing Conferene, Date: SEP 05-07, 2022, Location: Berlin, GERMANY, Patrocinadores: SPIE

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Publication Identifiers

DOI: 10.1117/12.2633872

SCOPUS: 2-s2.0-85142887341

Wos: WOS:000891771700006

Source Identifiers

ISSN: 0277-786X

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Characterizing Agri-Forestry Systems in Portugal Through High-Resolution Orthophotos and Convolutional Neural Networks

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Characterizing Agri-Forestry Systems in Portugal Through High-Resolution Orthophotos and Convolutional Neural Networks

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