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Artigo de periodico
Fully convolutional neural networks applied to large-scale marine morphology mapping (2023)
Arosio, Riccardo ; Hobley, Brandon ; Wheeler, Andrew J. ; Sacchetti, Fabio ; Conti, Luis Americo ; Furey, Thomas ; Lim, Aaron
Source: Frontiers in Marine Science. Unidade: EACH
Assunto: REDES NEURAIS
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AROSIO, Riccardo et al. Fully convolutional neural networks applied to large-scale marine morphology mapping. Frontiers in Marine Science, v. 10, p. 01-21, 2023Tradução . . Disponível em: https://doi.org/10.3389/fmars.2023.1228867. Acesso em: 06 nov. 2024.
APA
Arosio, R., Hobley, B., Wheeler, A. J., Sacchetti, F., Conti, L. A., Furey, T., & Lim, A. (2023). Fully convolutional neural networks applied to large-scale marine morphology mapping. Frontiers in Marine Science, 10, 01-21. doi:10.3389/fmars.2023.1228867
NLM
Arosio R, Hobley B, Wheeler AJ, Sacchetti F, Conti LA, Furey T, Lim A. Fully convolutional neural networks applied to large-scale marine morphology mapping [Internet]. Frontiers in Marine Science. 2023 ; 10 01-21.[citado 2024 nov. 06 ] Available from: https://doi.org/10.3389/fmars.2023.1228867
Vancouver
Arosio R, Hobley B, Wheeler AJ, Sacchetti F, Conti LA, Furey T, Lim A. Fully convolutional neural networks applied to large-scale marine morphology mapping [Internet]. Frontiers in Marine Science. 2023 ; 10 01-21.[citado 2024 nov. 06 ] Available from: https://doi.org/10.3389/fmars.2023.1228867
Artigo de periodico
Machine learning concepts applied to oral pathology and oral medicine: a convolutional neural networks' approach (2023)
Araujo, Anna Luiza Damaceno ; Silva, Viviane Mariano da ; Kudo, Maíra Suzuka ; Souza, Eduardo Santos Carlos de; Saldivia-Siracusa, Cristina ; Giraldo-Roldán, Daniela ; Lopes, Márcio Ajudarte ; Vargas, Pablo Agustin ; Khurram, Syed Ali ; Pearson, Alexander T ; Kowalski, Luiz Paulo ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Santos-Silva, Alan Roger dos ; Moraes, Matheus Cardoso
Source: Journal of Oral Pathology and Medicine. Unidades: FM, ICMC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, TECNOLOGIAS DA SAÚDE, NEOPLASIAS BUCAIS, NEOPLASIAS DE CABEÇA E PESCOÇO
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ARAUJO, Anna Luiza Damaceno et al. Machine learning concepts applied to oral pathology and oral medicine: a convolutional neural networks' approach. Journal of Oral Pathology and Medicine, v. 52, n. 2, p. 109-118, 2023Tradução . . Disponível em: https://doi.org/10.1111/jop.13397. Acesso em: 06 nov. 2024.
APA
Araujo, A. L. D., Silva, V. M. da, Kudo, M. S., Souza, E. S. C. de, Saldivia-Siracusa, C., Giraldo-Roldán, D., et al. (2023). Machine learning concepts applied to oral pathology and oral medicine: a convolutional neural networks' approach. Journal of Oral Pathology and Medicine, 52( 2), 109-118. doi:10.1111/jop.13397
NLM
Araujo ALD, Silva VM da, Kudo MS, Souza ESC de, Saldivia-Siracusa C, Giraldo-Roldán D, Lopes MA, Vargas PA, Khurram SA, Pearson AT, Kowalski LP, Carvalho ACP de LF de, Santos-Silva AR dos, Moraes MC. Machine learning concepts applied to oral pathology and oral medicine: a convolutional neural networks' approach [Internet]. Journal of Oral Pathology and Medicine. 2023 ; 52( 2): 109-118.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1111/jop.13397
Vancouver
Araujo ALD, Silva VM da, Kudo MS, Souza ESC de, Saldivia-Siracusa C, Giraldo-Roldán D, Lopes MA, Vargas PA, Khurram SA, Pearson AT, Kowalski LP, Carvalho ACP de LF de, Santos-Silva AR dos, Moraes MC. Machine learning concepts applied to oral pathology and oral medicine: a convolutional neural networks' approach [Internet]. Journal of Oral Pathology and Medicine. 2023 ; 52( 2): 109-118.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1111/jop.13397
Artigo de periodico
Scene designer: compositional sketch-based image retrieval with contrastive learning and an auxiliary synthesis task (2023)
Ribeiro, Leo Sampaio Ferraz ; Bui, Tu ; Collomosse, John ; Ponti, Moacir Antonelli
Source: Multimedia Tools and Applications. Unidade: ICMC
Subjects: RECUPERAÇÃO DA INFORMAÇÃO, RECONHECIMENTO DE IMAGEM, REDES NEURAIS, APRENDIZADO COMPUTACIONAL
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RIBEIRO, Leo Sampaio Ferraz et al. Scene designer: compositional sketch-based image retrieval with contrastive learning and an auxiliary synthesis task. Multimedia Tools and Applications, v. 82, n. 24, p. 38117-38139, 2023Tradução . . Disponível em: https://doi.org/10.1007/s11042-022-14282-0. Acesso em: 06 nov. 2024.
APA
Ribeiro, L. S. F., Bui, T., Collomosse, J., & Ponti, M. A. (2023). Scene designer: compositional sketch-based image retrieval with contrastive learning and an auxiliary synthesis task. Multimedia Tools and Applications, 82( 24), 38117-38139. doi:10.1007/s11042-022-14282-0
NLM
Ribeiro LSF, Bui T, Collomosse J, Ponti MA. Scene designer: compositional sketch-based image retrieval with contrastive learning and an auxiliary synthesis task [Internet]. Multimedia Tools and Applications. 2023 ; 82( 24): 38117-38139.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1007/s11042-022-14282-0
Vancouver
Ribeiro LSF, Bui T, Collomosse J, Ponti MA. Scene designer: compositional sketch-based image retrieval with contrastive learning and an auxiliary synthesis task [Internet]. Multimedia Tools and Applications. 2023 ; 82( 24): 38117-38139.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1007/s11042-022-14282-0
Artigo de periodico
Land use policies and their effects on brazilian farming production (2023)
El Batti, Matheus Mansour; Machado, Pedro Gerber ; Hawkes, Adam ; Ribeiro, Celma
Source: Journal for Nature Conservation. Unidade: EP
Subjects: SUSTENTABILIDADE, AGROPECUÁRIA, USO DO SOLO, REDES NEURAIS, REFLORESTAMENTO
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EL BATTI, Matheus Mansour et al. Land use policies and their effects on brazilian farming production. Journal for Nature Conservation, v. 73, p. 11 on-line, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.jnc.2023.126373. Acesso em: 06 nov. 2024.
APA
El Batti, M. M., Machado, P. G., Hawkes, A., & Ribeiro, C. (2023). Land use policies and their effects on brazilian farming production. Journal for Nature Conservation, 73, 11 on-line. doi:10.1016/j.jnc.2023.126373
NLM
El Batti MM, Machado PG, Hawkes A, Ribeiro C. Land use policies and their effects on brazilian farming production [Internet]. Journal for Nature Conservation. 2023 ; 73 11 on-line.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1016/j.jnc.2023.126373
Vancouver
El Batti MM, Machado PG, Hawkes A, Ribeiro C. Land use policies and their effects on brazilian farming production [Internet]. Journal for Nature Conservation. 2023 ; 73 11 on-line.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1016/j.jnc.2023.126373
Artigo de periodico
Clustered and deep echo state networks for signal noise reduction (2022)
Oliveira Junior, Laercio de; Stelzer, Florian; Liang, Zhao
Source: Machine Learning. Unidade: FFCLRP
Subjects: REDES COMPLEXAS, REDES NEURAIS, SISTEMAS DINÂMICOS
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OLIVEIRA JUNIOR, Laercio de e STELZER, Florian e LIANG, Zhao. Clustered and deep echo state networks for signal noise reduction. Machine Learning, v. 111, n. 8, p. 2885-2904, 2022Tradução . . Disponível em: https://doi.org/10.1007/s10994-022-06135-6. Acesso em: 06 nov. 2024.
APA
Oliveira Junior, L. de, Stelzer, F., & Liang, Z. (2022). Clustered and deep echo state networks for signal noise reduction. Machine Learning, 111( 8), 2885-2904. doi:10.1007/s10994-022-06135-6
NLM
Oliveira Junior L de, Stelzer F, Liang Z. Clustered and deep echo state networks for signal noise reduction [Internet]. Machine Learning. 2022 ; 111( 8): 2885-2904.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1007/s10994-022-06135-6
Vancouver
Oliveira Junior L de, Stelzer F, Liang Z. Clustered and deep echo state networks for signal noise reduction [Internet]. Machine Learning. 2022 ; 111( 8): 2885-2904.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1007/s10994-022-06135-6
Artigo de periodico
Neural network training fingerprint: visual analytics of the training process in classification neural networks (2022)
Ferreira, Martha Dais ; Cantareira, Gabriel Dias ; Mello, Rodrigo Fernandes de ; Paulovich, Fernando Vieira
Source: Journal of Visualization. Unidade: ICMC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, VISUALIZAÇÃO
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FERREIRA, Martha Dais et al. Neural network training fingerprint: visual analytics of the training process in classification neural networks. Journal of Visualization, v. 25, n. 3, p. 593-612, 2022Tradução . . Disponível em: https://doi.org/10.1007/s12650-021-00809-4. Acesso em: 06 nov. 2024.
APA
Ferreira, M. D., Cantareira, G. D., Mello, R. F. de, & Paulovich, F. V. (2022). Neural network training fingerprint: visual analytics of the training process in classification neural networks. Journal of Visualization, 25( 3), 593-612. doi:10.1007/s12650-021-00809-4
NLM
Ferreira MD, Cantareira GD, Mello RF de, Paulovich FV. Neural network training fingerprint: visual analytics of the training process in classification neural networks [Internet]. Journal of Visualization. 2022 ; 25( 3): 593-612.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1007/s12650-021-00809-4
Vancouver
Ferreira MD, Cantareira GD, Mello RF de, Paulovich FV. Neural network training fingerprint: visual analytics of the training process in classification neural networks [Internet]. Journal of Visualization. 2022 ; 25( 3): 593-612.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1007/s12650-021-00809-4
Artigo de periodico
findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM (2022)
Chojnowski, Grzegorz ; Simpkin, Adam J.; Leonardo, Diego Antonio; Seifert-Davila, Wolfram ; Vivas-Ruiz, Dan E.; Keegan, Ronan M.; Rigden, Daniel J.
Source: IUCrJ. Unidade: IFSC
Subjects: PROTEÍNAS, BIOINFORMÁTICA, REDES NEURAIS
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ABNT
CHOJNOWSKI, Grzegorz et al. findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM. IUCrJ, v. 9, n. Ja 2022, p. 86-97, 2022Tradução . . Disponível em: https://doi.org/10.1107/S2052252521011088. Acesso em: 06 nov. 2024.
APA
Chojnowski, G., Simpkin, A. J., Leonardo, D. A., Seifert-Davila, W., Vivas-Ruiz, D. E., Keegan, R. M., & Rigden, D. J. (2022). findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM. IUCrJ, 9( Ja 2022), 86-97. doi:10.1107/S2052252521011088
NLM
Chojnowski G, Simpkin AJ, Leonardo DA, Seifert-Davila W, Vivas-Ruiz DE, Keegan RM, Rigden DJ. findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM [Internet]. IUCrJ. 2022 ; 9( Ja 2022): 86-97.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1107/S2052252521011088
Vancouver
Chojnowski G, Simpkin AJ, Leonardo DA, Seifert-Davila W, Vivas-Ruiz DE, Keegan RM, Rigden DJ. findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM [Internet]. IUCrJ. 2022 ; 9( Ja 2022): 86-97.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1107/S2052252521011088
Relatorio tecnico
Plastic neural network with transmission delays promotes equivalence between function and structure (2022)
Protachevicz, Paulo Ricardo ; Borges, F. S.; Batista, A. M.; Baptista, M. S.; Macau, E. E. N.; Lameu, E. L.; Caldas, Iberê Luiz
Unidade: IF
Subjects: TOPOLOGIA, REDES NEURAIS
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ABNT
PROTACHEVICZ, Paulo Ricardo et al. Plastic neural network with transmission delays promotes equivalence between function and structure. . São Paulo: Instituto de Física, Universidade de São Paulo. Disponível em: https://arxiv.org/pdf/2211.05644.pdf. Acesso em: 06 nov. 2024. , 2022
APA
Protachevicz, P. R., Borges, F. S., Batista, A. M., Baptista, M. S., Macau, E. E. N., Lameu, E. L., & Caldas, I. L. (2022). Plastic neural network with transmission delays promotes equivalence between function and structure. São Paulo: Instituto de Física, Universidade de São Paulo. Recuperado de https://arxiv.org/pdf/2211.05644.pdf
NLM
Protachevicz PR, Borges FS, Batista AM, Baptista MS, Macau EEN, Lameu EL, Caldas IL. Plastic neural network with transmission delays promotes equivalence between function and structure [Internet]. 2022 ;[citado 2024 nov. 06 ] Available from: https://arxiv.org/pdf/2211.05644.pdf
Vancouver
Protachevicz PR, Borges FS, Batista AM, Baptista MS, Macau EEN, Lameu EL, Caldas IL. Plastic neural network with transmission delays promotes equivalence between function and structure [Internet]. 2022 ;[citado 2024 nov. 06 ] Available from: https://arxiv.org/pdf/2211.05644.pdf
Trabalho de evento
Scene Designer: a unified model for scene search and synthesis from sketch (2021)
Ribeiro, Leo Sampaio Ferraz ; Bui, Tu ; Collomosse, John ; Ponti, Moacir Antonelli
Source: Proceedings. Conference titles: IEEE/CVF International Conference on Computer Vision Workshops - ICCVW. Unidade: ICMC
Subjects: RECONHECIMENTO DE IMAGEM, REDES NEURAIS, APRENDIZADO COMPUTACIONAL
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ABNT
RIBEIRO, Leo Sampaio Ferraz et al. Scene Designer: a unified model for scene search and synthesis from sketch. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/ICCVW54120.2021.00275. Acesso em: 06 nov. 2024.
APA
Ribeiro, L. S. F., Bui, T., Collomosse, J., & Ponti, M. A. (2021). Scene Designer: a unified model for scene search and synthesis from sketch. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICCVW54120.2021.00275
NLM
Ribeiro LSF, Bui T, Collomosse J, Ponti MA. Scene Designer: a unified model for scene search and synthesis from sketch [Internet]. Proceedings. 2021 ;[citado 2024 nov. 06 ] Available from: https://doi.org/10.1109/ICCVW54120.2021.00275
Vancouver
Ribeiro LSF, Bui T, Collomosse J, Ponti MA. Scene Designer: a unified model for scene search and synthesis from sketch [Internet]. Proceedings. 2021 ;[citado 2024 nov. 06 ] Available from: https://doi.org/10.1109/ICCVW54120.2021.00275
Artigo de periodico
Learning image features with fewer labels using a semi-supervised deep convolutional network (2020)
Santos, Fernando Pereira dos ; Zor, Cemre ; Kittler, Josef ; Ponti, Moacir Antonelli
Source: Neural Networks. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, RECONHECIMENTO DE PADRÕES
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SANTOS, Fernando Pereira dos et al. Learning image features with fewer labels using a semi-supervised deep convolutional network. Neural Networks, v. 132, p. 131-143, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.neunet.2020.08.016. Acesso em: 06 nov. 2024.
APA
Santos, F. P. dos, Zor, C., Kittler, J., & Ponti, M. A. (2020). Learning image features with fewer labels using a semi-supervised deep convolutional network. Neural Networks, 132, 131-143. doi:10.1016/j.neunet.2020.08.016
NLM
Santos FP dos, Zor C, Kittler J, Ponti MA. Learning image features with fewer labels using a semi-supervised deep convolutional network [Internet]. Neural Networks. 2020 ; 132 131-143.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1016/j.neunet.2020.08.016
Vancouver
Santos FP dos, Zor C, Kittler J, Ponti MA. Learning image features with fewer labels using a semi-supervised deep convolutional network [Internet]. Neural Networks. 2020 ; 132 131-143.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1016/j.neunet.2020.08.016
Trabalho de evento
Unveiling Parkinson's disease features from a primate model with deep neural networks (2020)
Ranieri, Caetano Mazzoni ; Moioli, Renan Cipriano ; Romero, Roseli Aparecida Francelin ; Araújo, Mariana F. P. de; Santana, Maxwell Barbosa de ; Pimentel, Jhielson Montino ; Vargas, Patrícia Amâncio
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, ELETROENCEFALOGRAFIA, DOENÇA DE PARKINSON, NEUROCIÊNCIAS
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ABNT
RANIERI, Caetano Mazzoni et al. Unveiling Parkinson's disease features from a primate model with deep neural networks. 2020, Anais.. Piscataway: IEEE, 2020. Disponível em: https://doi.org/10.1109/IJCNN48605.2020.9207180. Acesso em: 06 nov. 2024.
APA
Ranieri, C. M., Moioli, R. C., Romero, R. A. F., Araújo, M. F. P. de, Santana, M. B. de, Pimentel, J. M., & Vargas, P. A. (2020). Unveiling Parkinson's disease features from a primate model with deep neural networks. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN48605.2020.9207180
NLM
Ranieri CM, Moioli RC, Romero RAF, Araújo MFP de, Santana MB de, Pimentel JM, Vargas PA. Unveiling Parkinson's disease features from a primate model with deep neural networks [Internet]. Proceedings. 2020 ;[citado 2024 nov. 06 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9207180
Vancouver
Ranieri CM, Moioli RC, Romero RAF, Araújo MFP de, Santana MB de, Pimentel JM, Vargas PA. Unveiling Parkinson's disease features from a primate model with deep neural networks [Internet]. Proceedings. 2020 ;[citado 2024 nov. 06 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9207180
Trabalho de evento
Uncovering human multimodal activity recognition with a deep learning approach (2020)
Ranieri, Caetano Mazzoni ; Vargas, Patrícia Amâncio; Romero, Roseli Aparecida Francelin
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, VISÃO COMPUTACIONAL, ROBÓTICA, INTERAÇÃO HOMEM-MÁQUINA
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ABNT
RANIERI, Caetano Mazzoni e VARGAS, Patrícia Amâncio e ROMERO, Roseli Aparecida Francelin. Uncovering human multimodal activity recognition with a deep learning approach. 2020, Anais.. Piscataway: IEEE, 2020. Disponível em: https://doi.org/10.1109/IJCNN48605.2020.9207255. Acesso em: 06 nov. 2024.
APA
Ranieri, C. M., Vargas, P. A., & Romero, R. A. F. (2020). Uncovering human multimodal activity recognition with a deep learning approach. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN48605.2020.9207255
NLM
Ranieri CM, Vargas PA, Romero RAF. Uncovering human multimodal activity recognition with a deep learning approach [Internet]. Proceedings. 2020 ;[citado 2024 nov. 06 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9207255
Vancouver
Ranieri CM, Vargas PA, Romero RAF. Uncovering human multimodal activity recognition with a deep learning approach [Internet]. Proceedings. 2020 ;[citado 2024 nov. 06 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9207255
Artigo de periodico
Bistable Firing Pattern in a Neural Network Model (2019)
Protachevicz, Paulo Ricardo; Borges, Fernando Silva ; Lameu, Ewandson Luiz ; Peng Ji; Iarosz, Kelly Cristiane ; Kihara, Alexandre Hiroaki ; Caldas, Iberê Luiz ; Szezech Jr., Jose D.; Murilo S. Baptista; Macau, Elbert E. N. ; Antonopoulos, Chris G.; Antonio M. Batista; Kurths, Jürgen
Source: Frontiers in Computational Neuroscience. Unidade: IF
Subjects: FÍSICA DE PLASMAS, SISTEMAS DINÂMICOS, BIOFÍSICA, MECÂNICA DOS FLUÍDOS, SISTEMAS DISSIPATIVO, EPILEPSIA, REDES NEURAIS
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ABNT
PROTACHEVICZ, Paulo Ricardo et al. Bistable Firing Pattern in a Neural Network Model. Frontiers in Computational Neuroscience, v. 13, 2019Tradução . . Disponível em: https://doi.org/10.3389/fncom.2019.00019. Acesso em: 06 nov. 2024.
APA
Protachevicz, P. R., Borges, F. S., Lameu, E. L., Peng Ji,, Iarosz, K. C., Kihara, A. H., et al. (2019). Bistable Firing Pattern in a Neural Network Model. Frontiers in Computational Neuroscience, 13. doi:10.3389/fncom.2019.00019
NLM
Protachevicz PR, Borges FS, Lameu EL, Peng Ji, Iarosz KC, Kihara AH, Caldas IL, Szezech Jr. JD, Murilo S. Baptista, Macau EEN, Antonopoulos CG, Antonio M. Batista, Kurths J. Bistable Firing Pattern in a Neural Network Model [Internet]. Frontiers in Computational Neuroscience. 2019 ; 13[citado 2024 nov. 06 ] Available from: https://doi.org/10.3389/fncom.2019.00019
Vancouver
Protachevicz PR, Borges FS, Lameu EL, Peng Ji, Iarosz KC, Kihara AH, Caldas IL, Szezech Jr. JD, Murilo S. Baptista, Macau EEN, Antonopoulos CG, Antonio M. Batista, Kurths J. Bistable Firing Pattern in a Neural Network Model [Internet]. Frontiers in Computational Neuroscience. 2019 ; 13[citado 2024 nov. 06 ] Available from: https://doi.org/10.3389/fncom.2019.00019
Relatorio tecnico
Bistable ring pattern in a neural network model (2018)
Protachevicz, P. R.; Szezech Jr, J. D.; Batista, A. M.; Iarosz, K. C.; Baptista, M. S.; Borges, F. S.; Lameu, E. L.; Ji, P.; Kihara, A. H.; Kurths, J.; Macau, E. E. N.; Antonopoulos, C. G.; Caldas, Iberê Luiz
Unidade: IF
Subjects: FÍSICA DE PLASMAS, TOKAMAKS, REDES NEURAIS
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ABNT
PROTACHEVICZ, P. R. et al. Bistable ring pattern in a neural network model. . São Paulo: Instituto de Física, Universidade de São Paulo. Disponível em: https://arxiv.org/abs/1810.10142. Acesso em: 06 nov. 2024. , 2018
APA
Protachevicz, P. R., Szezech Jr, J. D., Batista, A. M., Iarosz, K. C., Baptista, M. S., Borges, F. S., et al. (2018). Bistable ring pattern in a neural network model. São Paulo: Instituto de Física, Universidade de São Paulo. Recuperado de https://arxiv.org/abs/1810.10142
NLM
Protachevicz PR, Szezech Jr JD, Batista AM, Iarosz KC, Baptista MS, Borges FS, Lameu EL, Ji P, Kihara AH, Kurths J, Macau EEN, Antonopoulos CG, Caldas IL. Bistable ring pattern in a neural network model [Internet]. 2018 ;[citado 2024 nov. 06 ] Available from: https://arxiv.org/abs/1810.10142
Vancouver
Protachevicz PR, Szezech Jr JD, Batista AM, Iarosz KC, Baptista MS, Borges FS, Lameu EL, Ji P, Kihara AH, Kurths J, Macau EEN, Antonopoulos CG, Caldas IL. Bistable ring pattern in a neural network model [Internet]. 2018 ;[citado 2024 nov. 06 ] Available from: https://arxiv.org/abs/1810.10142
Relatorio tecnico
Riddling: chimera's dilemma (2018)
Santos, V.; Szezech Jr, J. D.; Batista, A. M.; Iarosz, K. C.; Baptista, M. S.; Ren, H. P.; Grebogi, C.; Viana, R. L.; Maistrenko, Y. L.; Kurths, J.; Caldas, Iberê Luiz
Unidade: IF
Subjects: FÍSICA DE PLASMAS, TOKAMAKS, REDES NEURAIS
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ABNT
SANTOS, V. et al. Riddling: chimera's dilemma. . São Paulo: Instituto de Física, Universidade de São Paulo. Disponível em: https://arxiv.org/abs/1807.08668. Acesso em: 06 nov. 2024. , 2018
APA
Santos, V., Szezech Jr, J. D., Batista, A. M., Iarosz, K. C., Baptista, M. S., Ren, H. P., et al. (2018). Riddling: chimera's dilemma. São Paulo: Instituto de Física, Universidade de São Paulo. Recuperado de https://arxiv.org/abs/1807.08668
NLM
Santos V, Szezech Jr JD, Batista AM, Iarosz KC, Baptista MS, Ren HP, Grebogi C, Viana RL, Maistrenko YL, Kurths J, Caldas IL. Riddling: chimera's dilemma [Internet]. 2018 ;[citado 2024 nov. 06 ] Available from: https://arxiv.org/abs/1807.08668
Vancouver
Santos V, Szezech Jr JD, Batista AM, Iarosz KC, Baptista MS, Ren HP, Grebogi C, Viana RL, Maistrenko YL, Kurths J, Caldas IL. Riddling: chimera's dilemma [Internet]. 2018 ;[citado 2024 nov. 06 ] Available from: https://arxiv.org/abs/1807.08668
Relatorio tecnico
Transition from normal to ballistic diffusion in a one-dimensional impact system. (2018)
Livorati, André L. P.; Kroetz, Tiago; Leonel, Edson D.; Dettmann, Carl P.; Caldas, Iberê Luiz
Unidade: IF
Subjects: FÍSICA DE PLASMAS, TOKAMAKS, REDES NEURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LIVORATI, André L. P. et al. Transition from normal to ballistic diffusion in a one-dimensional impact system. . São Paulo: Instituto de Física, Universidade de São Paulo. Disponível em: https://arxiv.org/abs/1803.07159. Acesso em: 06 nov. 2024. , 2018
APA
Livorati, A. L. P., Kroetz, T., Leonel, E. D., Dettmann, C. P., & Caldas, I. L. (2018). Transition from normal to ballistic diffusion in a one-dimensional impact system. São Paulo: Instituto de Física, Universidade de São Paulo. Recuperado de https://arxiv.org/abs/1803.07159
NLM
Livorati ALP, Kroetz T, Leonel ED, Dettmann CP, Caldas IL. Transition from normal to ballistic diffusion in a one-dimensional impact system. [Internet]. 2018 ;[citado 2024 nov. 06 ] Available from: https://arxiv.org/abs/1803.07159
Vancouver
Livorati ALP, Kroetz T, Leonel ED, Dettmann CP, Caldas IL. Transition from normal to ballistic diffusion in a one-dimensional impact system. [Internet]. 2018 ;[citado 2024 nov. 06 ] Available from: https://arxiv.org/abs/1803.07159
Artigo de periodico
Spike timing-dependent plasticity induces non-trivial topology in the brain (2017)
Borges, Rafael Ribaski; Borges, Fernando da Silva; Lameu, Ewandson Luiz; Batista, Antonio Marcos; Iarosz, Kelly Cristiane; Caldas, Iberê Luiz ; Antonopoulose, C G; Baptista, Murilo da Silva
Source: Neural Networks. Unidade: IF
Subjects: REDES NEURAIS, SINCRONIZAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BORGES, Rafael Ribaski et al. Spike timing-dependent plasticity induces non-trivial topology in the brain. Neural Networks, v. 88, p. 58–64, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.neunet.2017.01.010. Acesso em: 06 nov. 2024.
APA
Borges, R. R., Borges, F. da S., Lameu, E. L., Batista, A. M., Iarosz, K. C., Caldas, I. L., et al. (2017). Spike timing-dependent plasticity induces non-trivial topology in the brain. Neural Networks, 88, 58–64. doi:10.1016/j.neunet.2017.01.010
NLM
Borges RR, Borges F da S, Lameu EL, Batista AM, Iarosz KC, Caldas IL, Antonopoulose CG, Baptista M da S. Spike timing-dependent plasticity induces non-trivial topology in the brain [Internet]. Neural Networks. 2017 ; 88 58–64.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1016/j.neunet.2017.01.010
Vancouver
Borges RR, Borges F da S, Lameu EL, Batista AM, Iarosz KC, Caldas IL, Antonopoulose CG, Baptista M da S. Spike timing-dependent plasticity induces non-trivial topology in the brain [Internet]. Neural Networks. 2017 ; 88 58–64.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1016/j.neunet.2017.01.010
Artigo de periodico
Reduction strategies for hierarchical multi-label classification in protein function prediction (2016)
Cerri, Ricardo; Barros, Rodrigo C; Carvalho, André Carlos Ponce de Leon Ferreira de ; Jin, Yaochu
Source: BMC Bioinformatics. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, REDES NEURAIS, RECONHECIMENTO DE PADRÕES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CERRI, Ricardo et al. Reduction strategies for hierarchical multi-label classification in protein function prediction. BMC Bioinformatics, v. 17, p. 1-24, 2016Tradução . . Disponível em: https://doi.org/10.1186/s12859-016-1232-1. Acesso em: 06 nov. 2024.
APA
Cerri, R., Barros, R. C., Carvalho, A. C. P. de L. F. de, & Jin, Y. (2016). Reduction strategies for hierarchical multi-label classification in protein function prediction. BMC Bioinformatics, 17, 1-24. doi:10.1186/s12859-016-1232-1
NLM
Cerri R, Barros RC, Carvalho ACP de LF de, Jin Y. Reduction strategies for hierarchical multi-label classification in protein function prediction [Internet]. BMC Bioinformatics. 2016 ; 17 1-24.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1186/s12859-016-1232-1
Vancouver
Cerri R, Barros RC, Carvalho ACP de LF de, Jin Y. Reduction strategies for hierarchical multi-label classification in protein function prediction [Internet]. BMC Bioinformatics. 2016 ; 17 1-24.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1186/s12859-016-1232-1
Trabalho de evento
Comparison with parametric optimization in credit card fraud detection (2008)
Gadi, Manoel Fernando Alonso; Wang , Xidi; Lago, Alair Pereira do
Source: Proceedings. Conference titles: International Conference on Machine Learning and Applications - ICMLA. Unidade: IME
Subjects: REDES NEURAIS, SISTEMAS IMUNOLÓGICOS ARTIFICIAIS, INFERÊNCIA BAYESIANA E REDES DE CRENÇA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GADI, Manoel Fernando Alonso e WANG , Xidi e LAGO, Alair Pereira do. Comparison with parametric optimization in credit card fraud detection. 2008, Anais.. Piscataway: IEEE, 2008. Disponível em: https://doi.org/10.1109/ICMLA.2008.59. Acesso em: 06 nov. 2024.
APA
Gadi, M. F. A., Wang , X., & Lago, A. P. do. (2008). Comparison with parametric optimization in credit card fraud detection. In Proceedings. Piscataway: IEEE. doi:10.1109/ICMLA.2008.59
NLM
Gadi MFA, Wang X, Lago AP do. Comparison with parametric optimization in credit card fraud detection [Internet]. Proceedings. 2008 ;[citado 2024 nov. 06 ] Available from: https://doi.org/10.1109/ICMLA.2008.59
Vancouver
Gadi MFA, Wang X, Lago AP do. Comparison with parametric optimization in credit card fraud detection [Internet]. Proceedings. 2008 ;[citado 2024 nov. 06 ] Available from: https://doi.org/10.1109/ICMLA.2008.59

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