A benchmarking protocol for SAR colorization: From regression to deep learning approaches.

Shen, Kangqing; Vivone, Gemine; Yang, Xiaoyuan; Lolli, Simone; Schmitt, Michael

Shen, Kangqing; Vivone, Gemine; Yang, Xiaoyuan; Lolli, Simone; Schmitt, Michael.

Afiliação

Shen K; School of Mathematical Sciences, Beihang University, Beijing, 102206, China.
Vivone G; Institute of Methodologies for Environmental Analysis, CNR-IMAA, Tito Scalo, 85050, Italy; National Biodiversity Future Center, NBFC, Palermo, 90133, Italy.
Yang X; School of Mathematical Sciences, Beihang University, Beijing, 102206, China; Key Laboratory of Mathematics, Information and Behavior, Ministry of Education, Beihang University, Beijing, 102206, China. Electronic address: xiaoyuanyang@vip.163.com.
Lolli S; Institute of Methodologies for Environmental Analysis, CNR-IMAA, Tito Scalo, 85050, Italy; CommSensLab, Department of Signal Theory and Communications, Polytechnic University of Catalonia, Barcelona, 08034, Spain.
Schmitt M; University of the Bundeswehr, Neubiberg, 85577, Germany.

Neural Netw ; 169: 698-712, 2024 Jan.

Article em En | MEDLINE | ID: mdl-37976594

Assuntos

Benchmarking; Aprendizado Profundo; Radar; Conhecimento

Palavras-chave

Colorization; Conditional generative adversarial network; Image-to-image translation; Regression models; Sentinel images; Synthetic aperture radar images

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Benchmarking / Aprendizado Profundo Idioma: En Revista: Neural Netw Assunto da revista: NEUROLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Estados Unidos

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