Source: Journal of Applied Remote Sensing. Unidades: IME, EP
Subjects: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS, RESERVATÓRIOS
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HAMIDISHAD, Nayereh e CÉSAR JÚNIOR, Roberto Marcondes. Man-made object segmentation around reservoirs by an end-to-end two-phase deep learning-based workflow. Journal of Applied Remote Sensing, v. 18, n. artigo 018502, p. 1-20, 2024Tradução . . Disponível em: https://doi.org/10.1117/1.JRS.18.018502. Acesso em: 28 ago. 2024.APA
Hamidishad, N., & César Júnior, R. M. (2024). Man-made object segmentation around reservoirs by an end-to-end two-phase deep learning-based workflow. Journal of Applied Remote Sensing, 18( artigo 018502), 1-20. doi:10.1117/1.JRS.18.018502NLM
Hamidishad N, César Júnior RM. Man-made object segmentation around reservoirs by an end-to-end two-phase deep learning-based workflow [Internet]. Journal of Applied Remote Sensing. 2024 ; 18( artigo 018502): 1-20.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1117/1.JRS.18.018502Vancouver
Hamidishad N, César Júnior RM. Man-made object segmentation around reservoirs by an end-to-end two-phase deep learning-based workflow [Internet]. Journal of Applied Remote Sensing. 2024 ; 18( artigo 018502): 1-20.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1117/1.JRS.18.018502