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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: 09 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. 09 ] 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. 09 ] Available from: https://doi.org/10.1007/s10489-025-06555-6
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: 09 nov. 2025.
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 2025 nov. 09 ] 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 2025 nov. 09 ] Available from: https://doi.org/10.1007/s10489-024-05466-2
Artigo de periodico
Incorporating hand-crafted features into deep learning models for motor imagery EEG-based classification (2023)
Bustios, Paul ; Rosa, João Luís Garcia
Source: Applied Intelligence. Unidade: ICMC
Subjects: REDES NEURAIS, APRENDIZAGEM PROFUNDA, ELETROENCEFALOGRAFIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BUSTIOS, Paul e ROSA, João Luís Garcia. Incorporating hand-crafted features into deep learning models for motor imagery EEG-based classification. Applied Intelligence, v. 53, n. 24, p. 30133-30147, 2023Tradução . . Disponível em: https://doi.org/10.1007/s10489-023-05134-x. Acesso em: 09 nov. 2025.
APA
Bustios, P., & Rosa, J. L. G. (2023). Incorporating hand-crafted features into deep learning models for motor imagery EEG-based classification. Applied Intelligence, 53( 24), 30133-30147. doi:10.1007/s10489-023-05134-x
NLM
Bustios P, Rosa JLG. Incorporating hand-crafted features into deep learning models for motor imagery EEG-based classification [Internet]. Applied Intelligence. 2023 ; 53( 24): 30133-30147.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1007/s10489-023-05134-x
Vancouver
Bustios P, Rosa JLG. Incorporating hand-crafted features into deep learning models for motor imagery EEG-based classification [Internet]. Applied Intelligence. 2023 ; 53( 24): 30133-30147.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1007/s10489-023-05134-x
Artigo de periodico
A new cognitive filtering approach based on Freeman K3 Neural Networks (2016)
Rosa, João Luís Garcia ; Piazentin, Denis R. M
Source: Applied Intelligence. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, REDES NEURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ROSA, João Luís Garcia e PIAZENTIN, Denis R. M. A new cognitive filtering approach based on Freeman K3 Neural Networks. Applied Intelligence, v. 45, n. 2, p. Se 2016, 2016Tradução . . Disponível em: https://doi.org/10.1007/s10489-016-0772-4. Acesso em: 09 nov. 2025.
APA
Rosa, J. L. G., & Piazentin, D. R. M. (2016). A new cognitive filtering approach based on Freeman K3 Neural Networks. Applied Intelligence, 45( 2), Se 2016. doi:10.1007/s10489-016-0772-4
NLM
Rosa JLG, Piazentin DRM. A new cognitive filtering approach based on Freeman K3 Neural Networks [Internet]. Applied Intelligence. 2016 ; 45( 2): Se 2016.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1007/s10489-016-0772-4
Vancouver
Rosa JLG, Piazentin DRM. A new cognitive filtering approach based on Freeman K3 Neural Networks [Internet]. Applied Intelligence. 2016 ; 45( 2): Se 2016.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1007/s10489-016-0772-4
Artigo de periodico
A self-organizing context-based approach to the tracking of multiple robot trajactories (2002)
Araújo, Aluízio Fausto Ribeiro; Barreto, Guilherme de Alencar
Source: Applied Intelligence. Unidade: EESC
Subjects: REDES NEURAIS, CONTROLADORES PROGRAMÁVEIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ARAÚJO, Aluízio Fausto Ribeiro e BARRETO, Guilherme de Alencar. A self-organizing context-based approach to the tracking of multiple robot trajactories. Applied Intelligence, v. 17, n. 1, p. 99-116, 2002Tradução . . Disponível em: http://200.179.60.195:8590/?sp.nextform=mainfrm.htm&sp.usernumber.p=644894. Acesso em: 09 nov. 2025.
APA
Araújo, A. F. R., & Barreto, G. de A. (2002). A self-organizing context-based approach to the tracking of multiple robot trajactories. Applied Intelligence, 17( 1), 99-116. Recuperado de http://200.179.60.195:8590/?sp.nextform=mainfrm.htm&sp.usernumber.p=644894
NLM
Araújo AFR, Barreto G de A. A self-organizing context-based approach to the tracking of multiple robot trajactories [Internet]. Applied Intelligence. 2002 ; 17( 1): 99-116.[citado 2025 nov. 09 ] Available from: http://200.179.60.195:8590/?sp.nextform=mainfrm.htm&sp.usernumber.p=644894
Vancouver
Araújo AFR, Barreto G de A. A self-organizing context-based approach to the tracking of multiple robot trajactories [Internet]. Applied Intelligence. 2002 ; 17( 1): 99-116.[citado 2025 nov. 09 ] Available from: http://200.179.60.195:8590/?sp.nextform=mainfrm.htm&sp.usernumber.p=644894

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