Assessment of vehicle category classification method based on optical curtains and convolutional neural networks (2024)
- Authors:
- USP affiliated authors: YOSHIOKA, LEOPOLDO RIDEKI - EP ; JUSTO FILHO, JOÃO FRANCISCO - EP ; BARREYRO, JOAQUIN - EP ; MARTE, CLAUDIO LUIZ - EP
- Unidade: EP
- DOI: 10.1109/ACCESS.2024.3410160
- Subjects: SISTEMAS DE TRANSPORTES; SENSORES ÓPTICOS; TRANSPORTE RODOVIÁRIO
- Language: Inglês
- Imprenta:
- Publisher place: Piscataway
- Date published: 2024
- Source:
- Título: IEEE Access
- ISSN: 2169-3536
- Volume/Número/Paginação/Ano: p. 1-13, 2024
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
- Licença: cc-by-nc-nd
-
ABNT
BARREYRO, Joaquin et al. Assessment of vehicle category classification method based on optical curtains and convolutional neural networks. IEEE Access, p. 1-13, 2024Tradução . . Disponível em: https://doi.org/10.1109/ACCESS.2024.3410160. Acesso em: 29 dez. 2025. -
APA
Barreyro, J., Yoshioka, L. R., Marte, C. L., Piccirillo, C. G., Santos, M. M. D. dos, & Justo Filho, J. F. (2024). Assessment of vehicle category classification method based on optical curtains and convolutional neural networks. IEEE Access, 1-13. doi:10.1109/ACCESS.2024.3410160 -
NLM
Barreyro J, Yoshioka LR, Marte CL, Piccirillo CG, Santos MMD dos, Justo Filho JF. Assessment of vehicle category classification method based on optical curtains and convolutional neural networks [Internet]. IEEE Access. 2024 ; 1-13.[citado 2025 dez. 29 ] Available from: https://doi.org/10.1109/ACCESS.2024.3410160 -
Vancouver
Barreyro J, Yoshioka LR, Marte CL, Piccirillo CG, Santos MMD dos, Justo Filho JF. Assessment of vehicle category classification method based on optical curtains and convolutional neural networks [Internet]. IEEE Access. 2024 ; 1-13.[citado 2025 dez. 29 ] Available from: https://doi.org/10.1109/ACCESS.2024.3410160 - Estimation of highway traffic service level based on module of intelligent transportation system and artificial intelligence
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Informações sobre o DOI: 10.1109/ACCESS.2024.3410160 (Fonte: oaDOI API)
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