A two-level Markov random field for road network extraction and its application with optical, SAR, and multitemporal data (2016)
- Authors:
- USP affiliated authors: HIRATA JUNIOR, ROBERTO - IME ; CESAR JUNIOR, ROBERTO MARCONDES - IME
- Unidade: IME
- DOI: 10.1080/01431161.2016.1201227
- Subjects: PROCESSAMENTO DE IMAGENS; CAMPOS ALEATÓRIOS MARKOVIANOS; IMAGEAMENTO DE SATÉLITE
- Language: Inglês
- Imprenta:
- Source:
- Título: International Journal of Remote Sensing
- ISSN: 1366-5901
- Volume/Número/Paginação/Ano: v. 37, n. 16, p. 3584-3610, 2016
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
PERCIANO, Talita e HIRATA JÚNIOR, Roberto e CÉSAR JÚNIOR, Roberto Marcondes. A two-level Markov random field for road network extraction and its application with optical, SAR, and multitemporal data. International Journal of Remote Sensing, v. 37, n. 16, p. 3584-3610, 2016Tradução . . Disponível em: https://doi.org/10.1080/01431161.2016.1201227. Acesso em: 12 fev. 2026. -
APA
Perciano, T., Hirata Júnior, R., & César Júnior, R. M. (2016). A two-level Markov random field for road network extraction and its application with optical, SAR, and multitemporal data. International Journal of Remote Sensing, 37( 16), 3584-3610. doi:10.1080/01431161.2016.1201227 -
NLM
Perciano T, Hirata Júnior R, César Júnior RM. A two-level Markov random field for road network extraction and its application with optical, SAR, and multitemporal data [Internet]. International Journal of Remote Sensing. 2016 ; 37( 16): 3584-3610.[citado 2026 fev. 12 ] Available from: https://doi.org/10.1080/01431161.2016.1201227 -
Vancouver
Perciano T, Hirata Júnior R, César Júnior RM. A two-level Markov random field for road network extraction and its application with optical, SAR, and multitemporal data [Internet]. International Journal of Remote Sensing. 2016 ; 37( 16): 3584-3610.[citado 2026 fev. 12 ] Available from: https://doi.org/10.1080/01431161.2016.1201227 - A backmapping approach for graph-based object tracking
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Informações sobre o DOI: 10.1080/01431161.2016.1201227 (Fonte: oaDOI API)
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