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Trabalho de evento-anais periodico
Full motion focus: convolutional module for improved left ventricle segmentation over 4D MRI (2022)
Lima, Daniel Mário de ; Graves, Catharine de Vita ; Gutierrez, Marco Antonio ; Machado, Bruno Brandoli ; Rodrigues Junior, José Fernando
Source: Lecture Notes in Computer Science. Conference titles: International Conference on Image Analysis and Processing - ICIAP. Unidades: EP, ICMC
Subjects: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS, DIAGNÓSTICO POR IMAGEM, DIAGNÓSTICO POR COMPUTADOR, TECNOLOGIAS DA SAÚDE, RESSONÂNCIA MAGNÉTICA, TESTES DE FUNÇÃO CARDÍACA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LIMA, Daniel Mário de et al. Full motion focus: convolutional module for improved left ventricle segmentation over 4D MRI. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-06427-2_37. Acesso em: 14 nov. 2024. , 2022
APA
Lima, D. M. de, Graves, C. de V., Gutierrez, M. A., Machado, B. B., & Rodrigues Junior, J. F. (2022). Full motion focus: convolutional module for improved left ventricle segmentation over 4D MRI. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-031-06427-2_37
NLM
Lima DM de, Graves C de V, Gutierrez MA, Machado BB, Rodrigues Junior JF. Full motion focus: convolutional module for improved left ventricle segmentation over 4D MRI [Internet]. Lecture Notes in Computer Science. 2022 ; 13231 438-450.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1007/978-3-031-06427-2_37
Vancouver
Lima DM de, Graves C de V, Gutierrez MA, Machado BB, Rodrigues Junior JF. Full motion focus: convolutional module for improved left ventricle segmentation over 4D MRI [Internet]. Lecture Notes in Computer Science. 2022 ; 13231 438-450.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1007/978-3-031-06427-2_37
Artigo de periodico
Sketch+ for visual and correlation-based exploratory data analysis: a case study with COVID-19 databases (2022)
Cazzolato, Mirela Teixeira ; Rodrigues, Lucas Santiago ; Ribeiro, Marcela Xavier ; Gutierrez, Marco Antonio ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Journal of Information and Data Management - JIDM. Unidades: EP, ICMC
Subjects: BANCO DE DADOS, RECUPERAÇÃO DA INFORMAÇÃO, VISUALIZAÇÃO, COVID-19
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela Teixeira et al. Sketch+ for visual and correlation-based exploratory data analysis: a case study with COVID-19 databases. Journal of Information and Data Management - JIDM, v. 13, n. 2, p. Se 2022, 2022Tradução . . Disponível em: https://doi.org/10.5753/jidm.2022.2484. Acesso em: 14 nov. 2024.
APA
Cazzolato, M. T., Rodrigues, L. S., Ribeiro, M. X., Gutierrez, M. A., Traina Junior, C., & Traina, A. J. M. (2022). Sketch+ for visual and correlation-based exploratory data analysis: a case study with COVID-19 databases. Journal of Information and Data Management - JIDM, 13( 2), Se 2022. doi:10.5753/jidm.2022.2484
NLM
Cazzolato MT, Rodrigues LS, Ribeiro MX, Gutierrez MA, Traina Junior C, Traina AJM. Sketch+ for visual and correlation-based exploratory data analysis: a case study with COVID-19 databases [Internet]. Journal of Information and Data Management - JIDM. 2022 ; 13( 2): Se 2022.[citado 2024 nov. 14 ] Available from: https://doi.org/10.5753/jidm.2022.2484
Vancouver
Cazzolato MT, Rodrigues LS, Ribeiro MX, Gutierrez MA, Traina Junior C, Traina AJM. Sketch+ for visual and correlation-based exploratory data analysis: a case study with COVID-19 databases [Internet]. Journal of Information and Data Management - JIDM. 2022 ; 13( 2): Se 2022.[citado 2024 nov. 14 ] Available from: https://doi.org/10.5753/jidm.2022.2484
Trabalho de evento-anais periodico
Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases (2022)
Aguiar, Erikson Júlio de ; Marcomini, Karem Daiane ; Quirino, Felipe Antunes; Gutierrez, Marco Antonio ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Proceedings of SPIE. Conference titles: SPIE Medical Imaging. Unidades: EP, ICMC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, TECNOLOGIAS DA SAÚDE, RADIOGRAFIA, COVID-19
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
AGUIAR, Erikson Júlio de et al. Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases. Proceedings of SPIE. Bellingham: International Society for Optical Engineering - SPIE. Disponível em: https://doi.org/10.1117/12.2611199. Acesso em: 14 nov. 2024. , 2022
APA
Aguiar, E. J. de, Marcomini, K. D., Quirino, F. A., Gutierrez, M. A., Traina Junior, C., & Traina, A. J. M. (2022). Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases. Proceedings of SPIE. Bellingham: International Society for Optical Engineering - SPIE. doi:10.1117/12.2611199
NLM
Aguiar EJ de, Marcomini KD, Quirino FA, Gutierrez MA, Traina Junior C, Traina AJM. Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases [Internet]. Proceedings of SPIE. 2022 ; 12033 120332P-1-120332P-7.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1117/12.2611199
Vancouver
Aguiar EJ de, Marcomini KD, Quirino FA, Gutierrez MA, Traina Junior C, Traina AJM. Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases [Internet]. Proceedings of SPIE. 2022 ; 12033 120332P-1-120332P-7.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1117/12.2611199
Trabalho de evento-anais periodico
A deep learning approach for COVID-19 screening and localization on chest x-ray images (2022)
Marcomini, Karem Daiane ; Cardenas, Diego Armando Cardona ; Traina, Agma Juci Machado ; Krieger, Jose Eduardo ; Gutierrez, Marco Antonio
Source: Proceedings of SPIE. Conference titles: SPIE Medical Imaging. Unidades: ICMC, FM, EP
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, TECNOLOGIAS DA SAÚDE, RADIOGRAFIA, COVID-19
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARCOMINI, Karem Daiane et al. A deep learning approach for COVID-19 screening and localization on chest x-ray images. Proceedings of SPIE. Bellingham: International Society for Optical Engineering - SPIE. Disponível em: https://doi.org/10.1117/12.2613177. Acesso em: 14 nov. 2024. , 2022
APA
Marcomini, K. D., Cardenas, D. A. C., Traina, A. J. M., Krieger, J. E., & Gutierrez, M. A. (2022). A deep learning approach for COVID-19 screening and localization on chest x-ray images. Proceedings of SPIE. Bellingham: International Society for Optical Engineering - SPIE. doi:10.1117/12.2613177
NLM
Marcomini KD, Cardenas DAC, Traina AJM, Krieger JE, Gutierrez MA. A deep learning approach for COVID-19 screening and localization on chest x-ray images [Internet]. Proceedings of SPIE. 2022 ; 12033 1203327-1-1203327-9.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1117/12.2613177
Vancouver
Marcomini KD, Cardenas DAC, Traina AJM, Krieger JE, Gutierrez MA. A deep learning approach for COVID-19 screening and localization on chest x-ray images [Internet]. Proceedings of SPIE. 2022 ; 12033 1203327-1-1203327-9.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1117/12.2613177
Artigo de periodico
FeatSet+: visual features extracted from public image datasets (2022)
Cazzolato, Mirela Teixeira ; Scabora, Lucas de Carvalho ; Zabot, Guilherme Felipe ; Gutierrez, Marco Antonio ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Journal of Information and Data Management - JIDM. Unidades: EP, ICMC
Subjects: BANCO DE DADOS MULTIMÍDIA, APRENDIZADO COMPUTACIONAL, RECUPERAÇÃO DA INFORMAÇÃO, RECONHECIMENTO DE IMAGEM
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela Teixeira et al. FeatSet+: visual features extracted from public image datasets. Journal of Information and Data Management - JIDM, v. 13, n. 1, p. 33-48, 2022Tradução . . Disponível em: https://doi.org/10.5753/jidm.2022.2328. Acesso em: 14 nov. 2024.
APA
Cazzolato, M. T., Scabora, L. de C., Zabot, G. F., Gutierrez, M. A., Traina Junior, C., & Traina, A. J. M. (2022). FeatSet+: visual features extracted from public image datasets. Journal of Information and Data Management - JIDM, 13( 1), 33-48. doi:10.5753/jidm.2022.2328
NLM
Cazzolato MT, Scabora L de C, Zabot GF, Gutierrez MA, Traina Junior C, Traina AJM. FeatSet+: visual features extracted from public image datasets [Internet]. Journal of Information and Data Management - JIDM. 2022 ; 13( 1): 33-48.[citado 2024 nov. 14 ] Available from: https://doi.org/10.5753/jidm.2022.2328
Vancouver
Cazzolato MT, Scabora L de C, Zabot GF, Gutierrez MA, Traina Junior C, Traina AJM. FeatSet+: visual features extracted from public image datasets [Internet]. Journal of Information and Data Management - JIDM. 2022 ; 13( 1): 33-48.[citado 2024 nov. 14 ] Available from: https://doi.org/10.5753/jidm.2022.2328
Artigo de periodico
LIG-Doctor: efficient patient trajectory prediction using bidirectional minimal gated-recurrent networks (2021)
Rodrigues Junior, José Fernando ; Gutierrez, Marco Antonio ; Spadon, Gabriel ; Machado, Bruno Brandoli ; Amer-Yahia, Sihem
Source: Information Sciences. Unidades: ICMC, EP
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), PROGNÓSTICO, TECNOLOGIAS DA SAÚDE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RODRIGUES JUNIOR, José Fernando et al. LIG-Doctor: efficient patient trajectory prediction using bidirectional minimal gated-recurrent networks. Information Sciences, v. 545, p. 813-827, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2020.09.024. Acesso em: 14 nov. 2024.
APA
Rodrigues Junior, J. F., Gutierrez, M. A., Spadon, G., Machado, B. B., & Amer-Yahia, S. (2021). LIG-Doctor: efficient patient trajectory prediction using bidirectional minimal gated-recurrent networks. Information Sciences, 545, 813-827. doi:10.1016/j.ins.2020.09.024
NLM
Rodrigues Junior JF, Gutierrez MA, Spadon G, Machado BB, Amer-Yahia S. LIG-Doctor: efficient patient trajectory prediction using bidirectional minimal gated-recurrent networks [Internet]. Information Sciences. 2021 ; 545 813-827.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1016/j.ins.2020.09.024
Vancouver
Rodrigues Junior JF, Gutierrez MA, Spadon G, Machado BB, Amer-Yahia S. LIG-Doctor: efficient patient trajectory prediction using bidirectional minimal gated-recurrent networks [Internet]. Information Sciences. 2021 ; 545 813-827.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1016/j.ins.2020.09.024
Trabalho de evento
FeatSet: a compilation of visual features extracted from public image datasets (2021)
Cazzolato, Mirela Teixeira ; Scabora, Lucas de Carvalho ; Zabot, Guilherme Felipe ; Gutierrez, Marco Antonio ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Anais. Conference titles: Simpósio Brasileiro de Banco de Dados - SBBD. Unidades: EP, ICMC
Subjects: BANCO DE DADOS MULTIMÍDIA, APRENDIZADO COMPUTACIONAL, RECUPERAÇÃO DA INFORMAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela Teixeira et al. FeatSet: a compilation of visual features extracted from public image datasets. 2021, Anais.. Porto Alegre: SBC, 2021. Disponível em: https://doi.org/10.5753/dsw.2021.17417. Acesso em: 14 nov. 2024.
APA
Cazzolato, M. T., Scabora, L. de C., Zabot, G. F., Gutierrez, M. A., Traina Junior, C., & Traina, A. J. M. (2021). FeatSet: a compilation of visual features extracted from public image datasets. In Anais. Porto Alegre: SBC. doi:10.5753/dsw.2021.17417
NLM
Cazzolato MT, Scabora L de C, Zabot GF, Gutierrez MA, Traina Junior C, Traina AJM. FeatSet: a compilation of visual features extracted from public image datasets [Internet]. Anais. 2021 ;[citado 2024 nov. 14 ] Available from: https://doi.org/10.5753/dsw.2021.17417
Vancouver
Cazzolato MT, Scabora L de C, Zabot GF, Gutierrez MA, Traina Junior C, Traina AJM. FeatSet: a compilation of visual features extracted from public image datasets [Internet]. Anais. 2021 ;[citado 2024 nov. 14 ] Available from: https://doi.org/10.5753/dsw.2021.17417
Trabalho de evento
Similarity search and correlation-based exploratory analysis in EHRs: a case study with COVID-19 databases (2021)
Cazzolato, Mirela Teixeira ; Rodrigues, Lucas Santiago ; Ribeiro, Marcela Xavier ; Gutierrez, Marco Antonio ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Anais. Conference titles: Simpósio Brasileiro de Bancos de Dados - SBBD. Unidades: EP, ICMC
Subjects: BANCO DE DADOS, RECUPERAÇÃO DA INFORMAÇÃO, REGISTROS MÉDICOS, COVID-19
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela Teixeira et al. Similarity search and correlation-based exploratory analysis in EHRs: a case study with COVID-19 databases. 2021, Anais.. Porto Alegre: SBC, 2021. Disponível em: https://sol.sbc.org.br/index.php/sbbd/article/view/17863. Acesso em: 14 nov. 2024.
APA
Cazzolato, M. T., Rodrigues, L. S., Ribeiro, M. X., Gutierrez, M. A., Traina Junior, C., & Traina, A. J. M. (2021). Similarity search and correlation-based exploratory analysis in EHRs: a case study with COVID-19 databases. In Anais. Porto Alegre: SBC. Recuperado de https://sol.sbc.org.br/index.php/sbbd/article/view/17863
NLM
Cazzolato MT, Rodrigues LS, Ribeiro MX, Gutierrez MA, Traina Junior C, Traina AJM. Similarity search and correlation-based exploratory analysis in EHRs: a case study with COVID-19 databases [Internet]. Anais. 2021 ;[citado 2024 nov. 14 ] Available from: https://sol.sbc.org.br/index.php/sbbd/article/view/17863
Vancouver
Cazzolato MT, Rodrigues LS, Ribeiro MX, Gutierrez MA, Traina Junior C, Traina AJM. Similarity search and correlation-based exploratory analysis in EHRs: a case study with COVID-19 databases [Internet]. Anais. 2021 ;[citado 2024 nov. 14 ] Available from: https://sol.sbc.org.br/index.php/sbbd/article/view/17863

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