In-orbit demonstration of a re-trainable machine learning payload for processing optical imagery.

Mateo-Garcia, Gonzalo; Veitch-Michaelis, Josh; Purcell, Cormac; Longepe, Nicolas; Reid, Simon; Anlind, Alice; Bruhn, Fredrik; Parr, James; Mathieu, Pierre Philippe

Mateo-Garcia, Gonzalo; Veitch-Michaelis, Josh; Purcell, Cormac; Longepe, Nicolas; Reid, Simon; Anlind, Alice; Bruhn, Fredrik; Parr, James; Mathieu, Pierre Philippe.

Afiliação

Mateo-Garcia G; Trillium Technologies Ltd., 27-29 South Lambeth Road, London, SW8 1SZ, UK. gonzalo@trillium.tech.
Veitch-Michaelis J; Image Processing Laboratory, University of Valencia, Valencia, Spain. gonzalo@trillium.tech.
Purcell C; Trillium Technologies Ltd., 27-29 South Lambeth Road, London, SW8 1SZ, UK.
Longepe N; Department of Computer Science, ETH Zurich, Zurich, Switzerland.
Reid S; Trillium Technologies Ltd., 27-29 South Lambeth Road, London, SW8 1SZ, UK.
Anlind A; School of Computer Science and Engineering, University of New South Wales (UNSW), Sydney, Australia.
Bruhn F; Phi-Lab Explore Office, European Space Agency (ESA), Frascati, Italy.
Parr J; D-Orbit SpA, Viale Risorgimento, 57, 22073, Fino Mornasco, Como, Italy.
Mathieu PP; Unibap AB (Publ.), Kungsängsgatan 12, 753 22, Uppsala, Sweden.

Sci Rep ; 13(1): 10391, 2023 Jun 27.

Article em En | MEDLINE | ID: mdl-37369699

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Rep Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido

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