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Artigo de periodico
A deep learning workflow enhanced with optical flow fields for flood risk estimation (2024)
Ranieri, Caetano Mazzoni ; Souza, Thais Luiza Donega e ; Nishijima, Marislei ; Krishnamachari, Bhaskar ; Ueyama, Jó
Source: Applied Intelligence. Unidades: ICMC, IRI, EACH
Subjects: ENCHENTES URBANAS, APRENDIZAGEM PROFUNDA, PROCESSAMENTO DE IMAGENS, VISÃO COMPUTACIONAL, REDES NEURAIS
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ABNT
RANIERI, Caetano Mazzoni et al. A deep learning workflow enhanced with optical flow fields for flood risk estimation. Applied Intelligence, v. 54, p. 5536-5557, 2024Tradução . . Disponível em: https://doi.org/10.1007/s10489-024-05466-2. Acesso em: 19 out. 2024.
APA
Ranieri, C. M., Souza, T. L. D. e, Nishijima, M., Krishnamachari, B., & Ueyama, J. (2024). A deep learning workflow enhanced with optical flow fields for flood risk estimation. Applied Intelligence, 54, 5536-5557. doi:10.1007/s10489-024-05466-2
NLM
Ranieri CM, Souza TLD e, Nishijima M, Krishnamachari B, Ueyama J. A deep learning workflow enhanced with optical flow fields for flood risk estimation [Internet]. Applied Intelligence. 2024 ; 54 5536-5557.[citado 2024 out. 19 ] Available from: https://doi.org/10.1007/s10489-024-05466-2
Vancouver
Ranieri CM, Souza TLD e, Nishijima M, Krishnamachari B, Ueyama J. A deep learning workflow enhanced with optical flow fields for flood risk estimation [Internet]. Applied Intelligence. 2024 ; 54 5536-5557.[citado 2024 out. 19 ] Available from: https://doi.org/10.1007/s10489-024-05466-2
Artigo de periodico
Water level identification with laser sensors, inertial units, and machine learning (2024)
Ranieri, Caetano Mazzoni ; Foletto, Angelo Victor Kraemer ; Garcia, Rodrigo Dutra ; Matos, Saulo Neves ; Medina, Maria Mercedes Gamboa ; Marcolino, Leandro Soriano ; Ueyama, Jó
Source: Engineering Applications of Artificial Intelligence. Unidades: EESC, ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ENCHENTES URBANAS, PREDIÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RANIERI, Caetano Mazzoni et al. Water level identification with laser sensors, inertial units, and machine learning. Engineering Applications of Artificial Intelligence, v. 127, p. 1-17, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.engappai.2023.107235. Acesso em: 19 out. 2024.
APA
Ranieri, C. M., Foletto, A. V. K., Garcia, R. D., Matos, S. N., Medina, M. M. G., Marcolino, L. S., & Ueyama, J. (2024). Water level identification with laser sensors, inertial units, and machine learning. Engineering Applications of Artificial Intelligence, 127, 1-17. doi:10.1016/j.engappai.2023.107235
NLM
Ranieri CM, Foletto AVK, Garcia RD, Matos SN, Medina MMG, Marcolino LS, Ueyama J. Water level identification with laser sensors, inertial units, and machine learning [Internet]. Engineering Applications of Artificial Intelligence. 2024 ; 127 1-17.[citado 2024 out. 19 ] Available from: https://doi.org/10.1016/j.engappai.2023.107235
Vancouver
Ranieri CM, Foletto AVK, Garcia RD, Matos SN, Medina MMG, Marcolino LS, Ueyama J. Water level identification with laser sensors, inertial units, and machine learning [Internet]. Engineering Applications of Artificial Intelligence. 2024 ; 127 1-17.[citado 2024 out. 19 ] Available from: https://doi.org/10.1016/j.engappai.2023.107235
Artigo de periodico
FLORAS: urban flash-flood prediction using a multivariate model (2023)
Brito, Lucas Augusto Vieira; Meneguette, Rodolfo Ipolito ; Grande, Robson E. De ; Ranieri, Caetano Mazzoni ; Ueyama, Jó
Source: Applied Intelligence. Unidade: ICMC
Subjects: MINERAÇÃO DE DADOS, ENCHENTES URBANAS, APRENDIZADO COMPUTACIONAL
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ABNT
BRITO, Lucas Augusto Vieira et al. FLORAS: urban flash-flood prediction using a multivariate model. Applied Intelligence, v. 53, p. 16107-16125, 2023Tradução . . Disponível em: https://doi.org/10.1007/s10489-022-04319-0. Acesso em: 19 out. 2024.
APA
Brito, L. A. V., Meneguette, R. I., Grande, R. E. D., Ranieri, C. M., & Ueyama, J. (2023). FLORAS: urban flash-flood prediction using a multivariate model. Applied Intelligence, 53, 16107-16125. doi:10.1007/s10489-022-04319-0
NLM
Brito LAV, Meneguette RI, Grande RED, Ranieri CM, Ueyama J. FLORAS: urban flash-flood prediction using a multivariate model [Internet]. Applied Intelligence. 2023 ; 53 16107-16125.[citado 2024 out. 19 ] Available from: https://doi.org/10.1007/s10489-022-04319-0
Vancouver
Brito LAV, Meneguette RI, Grande RED, Ranieri CM, Ueyama J. FLORAS: urban flash-flood prediction using a multivariate model [Internet]. Applied Intelligence. 2023 ; 53 16107-16125.[citado 2024 out. 19 ] Available from: https://doi.org/10.1007/s10489-022-04319-0
Artigo de periodico
Providing a greater precision of situational awareness of urban floods through multimodal fusion (2022)
Costa, Thiago Aparecido Gonçalves da ; Meneguette, Rodolfo Ipolito ; Ueyama, Jó
Source: Expert Systems With Applications. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ENCHENTES URBANAS, REDES SOCIAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COSTA, Thiago Aparecido Gonçalves da e MENEGUETTE, Rodolfo Ipolito e UEYAMA, Jó. Providing a greater precision of situational awareness of urban floods through multimodal fusion. Expert Systems With Applications, v. 188, p. 1-28, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2021.115923. Acesso em: 19 out. 2024.
APA
Costa, T. A. G. da, Meneguette, R. I., & Ueyama, J. (2022). Providing a greater precision of situational awareness of urban floods through multimodal fusion. Expert Systems With Applications, 188, 1-28. doi:10.1016/j.eswa.2021.115923
NLM
Costa TAG da, Meneguette RI, Ueyama J. Providing a greater precision of situational awareness of urban floods through multimodal fusion [Internet]. Expert Systems With Applications. 2022 ; 188 1-28.[citado 2024 out. 19 ] Available from: https://doi.org/10.1016/j.eswa.2021.115923
Vancouver
Costa TAG da, Meneguette RI, Ueyama J. Providing a greater precision of situational awareness of urban floods through multimodal fusion [Internet]. Expert Systems With Applications. 2022 ; 188 1-28.[citado 2024 out. 19 ] Available from: https://doi.org/10.1016/j.eswa.2021.115923
Artigo de periodico
A river flooding detection system based on deep learning and computer vision (2022)
Fernandes Junior, Francisco Erivaldo ; Nonato, Luis Gustavo ; Ueyama, Jó
Source: Multimedia Tools and Applications. Unidade: ICMC
Subjects: VISÃO COMPUTACIONAL, ENCHENTES URBANAS, SEMÂNTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FERNANDES JUNIOR, Francisco Erivaldo e NONATO, Luis Gustavo e UEYAMA, Jó. A river flooding detection system based on deep learning and computer vision. Multimedia Tools and Applications, v. 81, p. 40231-40251, 2022Tradução . . Disponível em: https://doi.org/10.1007/s11042-022-12813-3. Acesso em: 19 out. 2024.
APA
Fernandes Junior, F. E., Nonato, L. G., & Ueyama, J. (2022). A river flooding detection system based on deep learning and computer vision. Multimedia Tools and Applications, 81, 40231-40251. doi:10.1007/s11042-022-12813-3
NLM
Fernandes Junior FE, Nonato LG, Ueyama J. A river flooding detection system based on deep learning and computer vision [Internet]. Multimedia Tools and Applications. 2022 ; 81 40231-40251.[citado 2024 out. 19 ] Available from: https://doi.org/10.1007/s11042-022-12813-3
Vancouver
Fernandes Junior FE, Nonato LG, Ueyama J. A river flooding detection system based on deep learning and computer vision [Internet]. Multimedia Tools and Applications. 2022 ; 81 40231-40251.[citado 2024 out. 19 ] Available from: https://doi.org/10.1007/s11042-022-12813-3
Artigo de periodico
Flood risk mitigation and valve control in stormwater systems: state-space modeling, control algorithms, and case studies (2022)
Gomes Junior, Marcus Nóbrega; Giacomoni, Marcio H; Taha, Ahmad F.; Mendiondo, Eduardo Mario
Source: Journal of Water Resources Planning and Management. Unidade: EESC
Subjects: TEMPO-REAL, CONTROLE (TEORIA DE SISTEMAS E CONTROLE), DRENAGEM URBANA, ENCHENTES URBANAS, ENGENHARIA HIDRÁULICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GOMES JUNIOR, Marcus Nóbrega et al. Flood risk mitigation and valve control in stormwater systems: state-space modeling, control algorithms, and case studies. Journal of Water Resources Planning and Management, v. 148, n. 12, p. 1-19, 2022Tradução . . Disponível em: https://doi.org/10.1061/(ASCE)WR.1943-5452.0001588. Acesso em: 19 out. 2024.
APA
Gomes Junior, M. N., Giacomoni, M. H., Taha, A. F., & Mendiondo, E. M. (2022). Flood risk mitigation and valve control in stormwater systems: state-space modeling, control algorithms, and case studies. Journal of Water Resources Planning and Management, 148( 12), 1-19. doi:10.1061/(ASCE)WR.1943-5452.0001588
NLM
Gomes Junior MN, Giacomoni MH, Taha AF, Mendiondo EM. Flood risk mitigation and valve control in stormwater systems: state-space modeling, control algorithms, and case studies [Internet]. Journal of Water Resources Planning and Management. 2022 ; 148( 12): 1-19.[citado 2024 out. 19 ] Available from: https://doi.org/10.1061/(ASCE)WR.1943-5452.0001588
Vancouver
Gomes Junior MN, Giacomoni MH, Taha AF, Mendiondo EM. Flood risk mitigation and valve control in stormwater systems: state-space modeling, control algorithms, and case studies [Internet]. Journal of Water Resources Planning and Management. 2022 ; 148( 12): 1-19.[citado 2024 out. 19 ] Available from: https://doi.org/10.1061/(ASCE)WR.1943-5452.0001588
Artigo de periodico
Linking urban floods to citizen science and low impact development in poorly gauged basins under climate changes for dynamic resilience evaluation (2022)
Fava, Maria Clara ; Macedo, Marina Batalini de ; Buarque, Ana Carolina Sarmento ; Saraiva, Antonio Mauro ; Delbem, Alexandre Cláudio Botazzo ; Mendiondo, Eduardo Mario
Source: Water. Unidades: EP, ICMC, EESC
Subjects: ENCHENTES URBANAS, SIMULAÇÃO, ANÁLISE DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FAVA, Maria Clara et al. Linking urban floods to citizen science and low impact development in poorly gauged basins under climate changes for dynamic resilience evaluation. Water, v. 14, n. 9, p. 1-24, 2022Tradução . . Disponível em: https://doi.org/10.3390/w14091467. Acesso em: 19 out. 2024.
APA
Fava, M. C., Macedo, M. B. de, Buarque, A. C. S., Saraiva, A. M., Delbem, A. C. B., & Mendiondo, E. M. (2022). Linking urban floods to citizen science and low impact development in poorly gauged basins under climate changes for dynamic resilience evaluation. Water, 14( 9), 1-24. doi:10.3390/w14091467
NLM
Fava MC, Macedo MB de, Buarque ACS, Saraiva AM, Delbem ACB, Mendiondo EM. Linking urban floods to citizen science and low impact development in poorly gauged basins under climate changes for dynamic resilience evaluation [Internet]. Water. 2022 ; 14( 9): 1-24.[citado 2024 out. 19 ] Available from: https://doi.org/10.3390/w14091467
Vancouver
Fava MC, Macedo MB de, Buarque ACS, Saraiva AM, Delbem ACB, Mendiondo EM. Linking urban floods to citizen science and low impact development in poorly gauged basins under climate changes for dynamic resilience evaluation [Internet]. Water. 2022 ; 14( 9): 1-24.[citado 2024 out. 19 ] Available from: https://doi.org/10.3390/w14091467
Artigo de periodico
Memory-based pruning of deep neural networks for IoT devices applied to flood detection (2021)
Fernandes Junior, Francisco Erivaldo ; Nonato, Luis Gustavo ; Ranieri, Caetano Mazzoni ; Ueyama, Jó
Source: Sensors. Unidade: ICMC
Subjects: ENCHENTES URBANAS, REDES NEURAIS, INTERNET DAS COISAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FERNANDES JUNIOR, Francisco Erivaldo et al. Memory-based pruning of deep neural networks for IoT devices applied to flood detection. Sensors, v. 21, n. 22, p. 1-18, 2021Tradução . . Disponível em: https://doi.org/10.3390/s21227506. Acesso em: 19 out. 2024.
APA
Fernandes Junior, F. E., Nonato, L. G., Ranieri, C. M., & Ueyama, J. (2021). Memory-based pruning of deep neural networks for IoT devices applied to flood detection. Sensors, 21( 22), 1-18. doi:10.3390/s21227506
NLM
Fernandes Junior FE, Nonato LG, Ranieri CM, Ueyama J. Memory-based pruning of deep neural networks for IoT devices applied to flood detection [Internet]. Sensors. 2021 ; 21( 22): 1-18.[citado 2024 out. 19 ] Available from: https://doi.org/10.3390/s21227506
Vancouver
Fernandes Junior FE, Nonato LG, Ranieri CM, Ueyama J. Memory-based pruning of deep neural networks for IoT devices applied to flood detection [Internet]. Sensors. 2021 ; 21( 22): 1-18.[citado 2024 out. 19 ] Available from: https://doi.org/10.3390/s21227506

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