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Artigo de periodico
Respiratory rate regression in Holstein dairy cattle with deep neural networks: an evaluation on different body regions (2025)
Curti, Paula de Freitas ; Souza, André Moreira ; Kobayashi, Livia Lissa ; Castanheira, Aline Mello ; Pinto, Diógenes Lodi ; Ruiz, Alexandre Merlos ; Andrietta, Lucas Tassoni ; Balieiro, Júlio Cesar de Carvalho ; Rennó, Francisco Palma ; Sousa, Elaine Parros Machado de ; Ventura, Ricardo Vieira
Source: Computers and Electronics in Agriculture. Unidades: FMVZ, ICMC
Subjects: VISÃO COMPUTACIONAL, APRENDIZAGEM PROFUNDA, PECUÁRIA LEITEIRA, GADO HOLANDÊS, ZOOTECNIA DE PRECISÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CURTI, Paula de Freitas et al. Respiratory rate regression in Holstein dairy cattle with deep neural networks: an evaluation on different body regions. Computers and Electronics in Agriculture, v. 239, p. 1-9, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2025.110987. Acesso em: 28 nov. 2025.
APA
Curti, P. de F., Souza, A. M., Kobayashi, L. L., Castanheira, A. M., Pinto, D. L., Ruiz, A. M., et al. (2025). Respiratory rate regression in Holstein dairy cattle with deep neural networks: an evaluation on different body regions. Computers and Electronics in Agriculture, 239, 1-9. doi:10.1016/j.compag.2025.110987
NLM
Curti P de F, Souza AM, Kobayashi LL, Castanheira AM, Pinto DL, Ruiz AM, Andrietta LT, Balieiro JC de C, Rennó FP, Sousa EPM de, Ventura RV. Respiratory rate regression in Holstein dairy cattle with deep neural networks: an evaluation on different body regions [Internet]. Computers and Electronics in Agriculture. 2025 ; 239 1-9.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1016/j.compag.2025.110987
Vancouver
Curti P de F, Souza AM, Kobayashi LL, Castanheira AM, Pinto DL, Ruiz AM, Andrietta LT, Balieiro JC de C, Rennó FP, Sousa EPM de, Ventura RV. Respiratory rate regression in Holstein dairy cattle with deep neural networks: an evaluation on different body regions [Internet]. Computers and Electronics in Agriculture. 2025 ; 239 1-9.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1016/j.compag.2025.110987
Artigo de periodico
Deep learning solutions for audio event detection in a swine barn using environmental audio and weak labels (2025)
Souza, André Moreira ; Kobayashi, Livia Lissa ; Andrietta, Lucas Tassoni ; Garbossa, Cesar Augusto Pospissil ; Ventura, Ricardo Vieira ; Sousa, Elaine Parros Machado de
Source: Applied Intelligence. Unidades: FMVZ, ICMC
Subjects: APRENDIZAGEM PROFUNDA, VISÃO COMPUTACIONAL, PROCESSAMENTO DE SINAIS ACÚSTICOS, REDES NEURAIS, SUINOCULTURA, BEM-ESTAR DO ANIMAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUZA, André Moreira et al. Deep learning solutions for audio event detection in a swine barn using environmental audio and weak labels. Applied Intelligence, v. 55, n. 7, p. 1-12, 2025Tradução . . Disponível em: https://doi.org/10.1007/s10489-025-06555-6. Acesso em: 28 nov. 2025.
APA
Souza, A. M., Kobayashi, L. L., Andrietta, L. T., Garbossa, C. A. P., Ventura, R. V., & Sousa, E. P. M. de. (2025). Deep learning solutions for audio event detection in a swine barn using environmental audio and weak labels. Applied Intelligence, 55( 7), 1-12. doi:10.1007/s10489-025-06555-6
NLM
Souza AM, Kobayashi LL, Andrietta LT, Garbossa CAP, Ventura RV, Sousa EPM de. Deep learning solutions for audio event detection in a swine barn using environmental audio and weak labels [Internet]. Applied Intelligence. 2025 ; 55( 7): 1-12.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/s10489-025-06555-6
Vancouver
Souza AM, Kobayashi LL, Andrietta LT, Garbossa CAP, Ventura RV, Sousa EPM de. Deep learning solutions for audio event detection in a swine barn using environmental audio and weak labels [Internet]. Applied Intelligence. 2025 ; 55( 7): 1-12.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/s10489-025-06555-6
Artigo de periodico
Mining temporal rules from heterogeneous multivariate time series (2023)
Karasawa, Eliane Gniech ; Sousa, Elaine Parros Machado de
Source: Journal of Information and Data Management - JIDM. Unidade: ICMC
Subjects: MINERAÇÃO DE DADOS, ANÁLISE DE SÉRIES TEMPORAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
KARASAWA, Eliane Gniech e SOUSA, Elaine Parros Machado de. Mining temporal rules from heterogeneous multivariate time series. Journal of Information and Data Management - JIDM, v. 14, n. 2, p. 1-10, 2023Tradução . . Disponível em: https://doi.org/10.5753/jidm.2023.3232. Acesso em: 28 nov. 2025.
APA
Karasawa, E. G., & Sousa, E. P. M. de. (2023). Mining temporal rules from heterogeneous multivariate time series. Journal of Information and Data Management - JIDM, 14( 2), 1-10. doi:10.5753/jidm.2023.3232
NLM
Karasawa EG, Sousa EPM de. Mining temporal rules from heterogeneous multivariate time series [Internet]. Journal of Information and Data Management - JIDM. 2023 ; 14( 2): 1-10.[citado 2025 nov. 28 ] Available from: https://doi.org/10.5753/jidm.2023.3232
Vancouver
Karasawa EG, Sousa EPM de. Mining temporal rules from heterogeneous multivariate time series [Internet]. Journal of Information and Data Management - JIDM. 2023 ; 14( 2): 1-10.[citado 2025 nov. 28 ] Available from: https://doi.org/10.5753/jidm.2023.3232
Artigo de periodico
Multiclass classifier based on deep learning for detection of citrus disease using fluorescence imaging spectroscopy (2023)
Neves, Ruan Felipe de Oliveira; Wetterich, Caio Bruno; Sousa, Elaine Parros Machado de ; Marcassa, Luís Gustavo
Source: Laser Physics. Unidades: IFSC, ICMC
Subjects: IMAGEM, PRAGAS DE PLANTAS, ESPECTROSCOPIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NEVES, Ruan Felipe de Oliveira et al. Multiclass classifier based on deep learning for detection of citrus disease using fluorescence imaging spectroscopy. Laser Physics, v. 33, n. 5, p. 055602-1-055602-9, 2023Tradução . . Disponível em: https://doi.org/10.1088/1555-6611/acc6bd. Acesso em: 28 nov. 2025.
APA
Neves, R. F. de O., Wetterich, C. B., Sousa, E. P. M. de, & Marcassa, L. G. (2023). Multiclass classifier based on deep learning for detection of citrus disease using fluorescence imaging spectroscopy. Laser Physics, 33( 5), 055602-1-055602-9. doi:10.1088/1555-6611/acc6bd
NLM
Neves RF de O, Wetterich CB, Sousa EPM de, Marcassa LG. Multiclass classifier based on deep learning for detection of citrus disease using fluorescence imaging spectroscopy [Internet]. Laser Physics. 2023 ; 33( 5): 055602-1-055602-9.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1088/1555-6611/acc6bd
Vancouver
Neves RF de O, Wetterich CB, Sousa EPM de, Marcassa LG. Multiclass classifier based on deep learning for detection of citrus disease using fluorescence imaging spectroscopy [Internet]. Laser Physics. 2023 ; 33( 5): 055602-1-055602-9.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1088/1555-6611/acc6bd
Artigo de periodico
Practical implications of using non-relational databases to store large genomic data files and novel phenotypes (2022)
Souza, André Moreira ; Weigert, Rodrigo de Andrade Santos; Sousa, Elaine Parros Machado de ; Andrietta, Lucas Tassoni ; Ventura, Ricardo Vieira
Source: Journal of Animal Breeding and Genetics. Unidades: ICMC, FMVZ
Subjects: BANCO DE DADOS, GENÉTICA ANIMAL, GENÔMICA, FENÓTIPOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUZA, André Moreira et al. Practical implications of using non-relational databases to store large genomic data files and novel phenotypes. Journal of Animal Breeding and Genetics, v. 139, n. Ja 2022, p. 100-112, 2022Tradução . . Disponível em: https://doi.org/10.1111/jbg.12644. Acesso em: 28 nov. 2025.
APA
Souza, A. M., Weigert, R. de A. S., Sousa, E. P. M. de, Andrietta, L. T., & Ventura, R. V. (2022). Practical implications of using non-relational databases to store large genomic data files and novel phenotypes. Journal of Animal Breeding and Genetics, 139( Ja 2022), 100-112. doi:10.1111/jbg.12644
NLM
Souza AM, Weigert R de AS, Sousa EPM de, Andrietta LT, Ventura RV. Practical implications of using non-relational databases to store large genomic data files and novel phenotypes [Internet]. Journal of Animal Breeding and Genetics. 2022 ; 139( Ja 2022): 100-112.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1111/jbg.12644
Vancouver
Souza AM, Weigert R de AS, Sousa EPM de, Andrietta LT, Ventura RV. Practical implications of using non-relational databases to store large genomic data files and novel phenotypes [Internet]. Journal of Animal Breeding and Genetics. 2022 ; 139( Ja 2022): 100-112.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1111/jbg.12644

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