Gonçalves, Nathan Borges; Rosa, Diogo Martins; Valle, Dalton Freitas do; Smith, Marielle N; Dalagnol, Ricardo; Almeida, Danilo Roberti Alves de 
; Nelson, Bruce W; Stark, Scott C
Source: Ecological Informatics. Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, FLORESTAS TROPICAIS, SENSORIAMENTO REMOTO, TECNOLOGIA LIDAR, TOPOGRAFIA
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GONÇALVES, Nathan Borges et al. Revealing forest structural fingerprints: An integration of LiDAR and deep learning uncovers topographical influences on Central Amazon forests. Ecological Informatics, v. 81, p. 1-10, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.ecoinf.2024.102628. Acesso em: 09 nov. 2024.APA
Gonçalves, N. B., Rosa, D. M., Valle, D. F. do, Smith, M. N., Dalagnol, R., Almeida, D. R. A. de, et al. (2024). Revealing forest structural fingerprints: An integration of LiDAR and deep learning uncovers topographical influences on Central Amazon forests. Ecological Informatics, 81, 1-10. doi:10.1016/j.ecoinf.2024.102628NLM
Gonçalves NB, Rosa DM, Valle DF do, Smith MN, Dalagnol R, Almeida DRA de, Nelson BW, Stark SC. Revealing forest structural fingerprints: An integration of LiDAR and deep learning uncovers topographical influences on Central Amazon forests [Internet]. Ecological Informatics. 2024 ; 81 1-10.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.ecoinf.2024.102628Vancouver
Gonçalves NB, Rosa DM, Valle DF do, Smith MN, Dalagnol R, Almeida DRA de, Nelson BW, Stark SC. Revealing forest structural fingerprints: An integration of LiDAR and deep learning uncovers topographical influences on Central Amazon forests [Internet]. Ecological Informatics. 2024 ; 81 1-10.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.ecoinf.2024.102628
