Source: Remote Sensing. Unidade: ICMC
Subjects: SENSORIAMENTO REMOTO, REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, ANÁLISE DE SÉRIES TEMPORAIS, INCÊNDIOS FLORESTAIS
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LUZ, Andréa Eliza O et al. Mapping fire susceptibility in the brazilian Amazon forests using multitemporal remote sensing and time-varying unsupervised anomaly detection. Remote Sensing, v. 14, n. 10, p. 1-17, 2022Tradução . . Disponível em: https://doi.org/10.3390/rs14102429. Acesso em: 08 maio 2024.APA
Luz, A. E. O., Negri, R. G., Massi, K. G., Colnago, M., Silva, E. A. da, & Casaca, W. C. de O. (2022). Mapping fire susceptibility in the brazilian Amazon forests using multitemporal remote sensing and time-varying unsupervised anomaly detection. Remote Sensing, 14( 10), 1-17. doi:10.3390/rs14102429NLM
Luz AEO, Negri RG, Massi KG, Colnago M, Silva EA da, Casaca WC de O. Mapping fire susceptibility in the brazilian Amazon forests using multitemporal remote sensing and time-varying unsupervised anomaly detection [Internet]. Remote Sensing. 2022 ; 14( 10): 1-17.[citado 2024 maio 08 ] Available from: https://doi.org/10.3390/rs14102429Vancouver
Luz AEO, Negri RG, Massi KG, Colnago M, Silva EA da, Casaca WC de O. Mapping fire susceptibility in the brazilian Amazon forests using multitemporal remote sensing and time-varying unsupervised anomaly detection [Internet]. Remote Sensing. 2022 ; 14( 10): 1-17.[citado 2024 maio 08 ] Available from: https://doi.org/10.3390/rs14102429