MACHINE LEARNING FOR SMALL BODIES IN THE SOLAR SYSTEM

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorBelgrade Astronomical Observatory-
Autor(es): dc.contributorAdam Mickiewicz University-
Autor(es): dc.creatorCarruba, Valerio-
Autor(es): dc.creatorSmirnov, Evgeny-
Autor(es): dc.creatorOszkiewicz, Dagmara-
Data de aceite: dc.date.accessioned2025-08-21T23:44:48Z-
Data de disponibilização: dc.date.available2025-08-21T23:44:48Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2023-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1016/C2023-0-51021-3-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/307172-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/307172-
Descrição: dc.descriptionMachine Learning for Small Bodies in the Solar System provides the latest developments and methods in applications of Machine Learning (ML) and Artificial Intelligence (AI) to different aspects of Solar System bodies, including dynamics, physical properties, and detection algorithms. Offering a practical approach, the book encompasses a wide range of topics, providing both readers with essential tools and insights for use in researching asteroids, comets, moons, and Trans-Neptunian objects. The inclusion of codes and links to publicly available repositories further facilitates hands-on learning, enabling readers to put their newfound knowledge into practice. Machine Learning for Small Bodies in the Solar System serves as an invaluable reference for researchers working in the broad fields of Solar System bodies; both seasoned researchers seeking to enhance their understanding of ML and AI in the context of Solar System exploration or those just stepping into the field looking for direction on methodologies and techniques to apply ML and AI in their work.-
Descrição: dc.descriptionSão Paulo State University (UNESP) Department of Mathematics, SP-
Descrição: dc.descriptionBelgrade Astronomical Observatory-
Descrição: dc.descriptionAstronomical Observatory Institute Faculty of Physics and Astronomy Adam Mickiewicz University-
Descrição: dc.descriptionSão Paulo State University (UNESP) Department of Mathematics, SP-
Formato: dc.format1-312-
Idioma: dc.languageen-
Relação: dc.relationMachine Learning for Small Bodies in the Solar System-
???dc.source???: dc.sourceScopus-
Título: dc.titleMACHINE LEARNING FOR SMALL BODIES IN THE SOLAR SYSTEM-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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