Federated system for transport mode detection (2022)
- Authors:
- USP affiliated authors: MENEGUETTE, RODOLFO IPOLITO - ICMC ; UEYAMA, JO - ICMC
- Unidade: ICMC
- DOI: 10.3390/en15239256
- Subjects: REDES NEURAIS; TRANSPORTE URBANO; TELEFONIA MÓVEL; CIDADES INTELIGENTES
- Keywords: transport mode detection; Federated Learning; smartphone; artificial Neural Networks
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
CAVALCANTE, Iago Carvalho et al. Federated system for transport mode detection. Energies, v. 15, p. 1-17, 2022Tradução . . Disponível em: https://doi.org/10.3390/en15239256. Acesso em: 12 fev. 2026. -
APA
Cavalcante, I. C., Meneguette, R. I., Torres, R. H., Mano, L. Y., Gonçalves, V. P., Ueyama, J., et al. (2022). Federated system for transport mode detection. Energies, 15, 1-17. doi:10.3390/en15239256 -
NLM
Cavalcante IC, Meneguette RI, Torres RH, Mano LY, Gonçalves VP, Ueyama J, Pessin G, Nze GDA, Rocha Filho GP. Federated system for transport mode detection [Internet]. Energies. 2022 ; 15 1-17.[citado 2026 fev. 12 ] Available from: https://doi.org/10.3390/en15239256 -
Vancouver
Cavalcante IC, Meneguette RI, Torres RH, Mano LY, Gonçalves VP, Ueyama J, Pessin G, Nze GDA, Rocha Filho GP. Federated system for transport mode detection [Internet]. Energies. 2022 ; 15 1-17.[citado 2026 fev. 12 ] Available from: https://doi.org/10.3390/en15239256 - Vehicular edge computing: architecture, resource management, security, and challenges
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Informações sobre o DOI: 10.3390/en15239256 (Fonte: oaDOI API)
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