A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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SILVA, Endi Daniel Coelho e TRAINA, Agma Juci Machado. BoCS: image retrieval using explicable methods. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/SIBGRAPI59091.2023.10347171. Acesso em: 03 maio 2024.
APA
Silva, E. D. C., & Traina, A. J. M. (2023). BoCS: image retrieval using explicable methods. In Proceedings. Piscataway: IEEE. doi:10.1109/SIBGRAPI59091.2023.10347171
NLM
Silva EDC, Traina AJM. BoCS: image retrieval using explicable methods [Internet]. Proceedings. 2023 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/SIBGRAPI59091.2023.10347171
Vancouver
Silva EDC, Traina AJM. BoCS: image retrieval using explicable methods [Internet]. Proceedings. 2023 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/SIBGRAPI59091.2023.10347171
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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CAZZOLATO, Mirela Teixeira et al. Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools. 2023, Anais.. Los Alamitos: IEEE, 2023. Disponível em: https://doi.org/10.1109/CBMS58004.2023.00202. Acesso em: 03 maio 2024.
APA
Cazzolato, M. T., Gutierrez, M. A., Traina Junior, C., Faloutsos, C., & Traina, A. J. M. (2023). Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS58004.2023.00202
NLM
Cazzolato MT, Gutierrez MA, Traina Junior C, Faloutsos C, Traina AJM. Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools [Internet]. Proceedings. 2023 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00202
Vancouver
Cazzolato MT, Gutierrez MA, Traina Junior C, Faloutsos C, Traina AJM. Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools [Internet]. Proceedings. 2023 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00202
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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AGUIAR, Erikson Júlio de et al. Assessing vulnerabilities of deep learning explainability in medical image analysis under adversarial settings. 2023, Anais.. Los Alamitos: IEEE, 2023. Disponível em: https://doi.org/10.1109/CBMS58004.2023.00184. Acesso em: 03 maio 2024.
APA
Aguiar, E. J. de, Costa, M. V. L., Traina Junior, C., & Traina, A. J. M. (2023). Assessing vulnerabilities of deep learning explainability in medical image analysis under adversarial settings. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS58004.2023.00184
NLM
Aguiar EJ de, Costa MVL, Traina Junior C, Traina AJM. Assessing vulnerabilities of deep learning explainability in medical image analysis under adversarial settings [Internet]. Proceedings. 2023 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00184
Vancouver
Aguiar EJ de, Costa MVL, Traina Junior C, Traina AJM. Assessing vulnerabilities of deep learning explainability in medical image analysis under adversarial settings [Internet]. Proceedings. 2023 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00184
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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COSTA, Márcus Vinícius Lobo et al. A deep learning-based radiomics approach for COVID-19 detection from CXR images using ensemble learning model. 2023, Anais.. Los Alamitos: IEEE, 2023. Disponível em: https://doi.org/10.1109/CBMS58004.2023.00272. Acesso em: 03 maio 2024.
APA
Costa, M. V. L., Aguiar, E. J. de, Rodrigues, L. S., Ramos, J. da S., Traina Junior, C., & Traina, A. J. M. (2023). A deep learning-based radiomics approach for COVID-19 detection from CXR images using ensemble learning model. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS58004.2023.00272
NLM
Costa MVL, Aguiar EJ de, Rodrigues LS, Ramos J da S, Traina Junior C, Traina AJM. A deep learning-based radiomics approach for COVID-19 detection from CXR images using ensemble learning model [Internet]. Proceedings. 2023 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00272
Vancouver
Costa MVL, Aguiar EJ de, Rodrigues LS, Ramos J da S, Traina Junior C, Traina AJM. A deep learning-based radiomics approach for COVID-19 detection from CXR images using ensemble learning model [Internet]. Proceedings. 2023 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00272
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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BÊDO, Marcos Vinícius Naves et al. Wia-Spine: a CBIR environment with embedded radiomic features to assess fragility fractures. 2022, Anais.. Los Alamitos: IEEE, 2022. Disponível em: https://doi.org/10.1109/CBMS55023.2022.00020. Acesso em: 03 maio 2024.
APA
Bêdo, M. V. N., Ramos, J. da S., Traina, A. J. M., Traina Junior, C., Nogueira-Barbosa, M. H., & Azevedo-Marques, P. M. de. (2022). Wia-Spine: a CBIR environment with embedded radiomic features to assess fragility fractures. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS55023.2022.00020
NLM
Bêdo MVN, Ramos J da S, Traina AJM, Traina Junior C, Nogueira-Barbosa MH, Azevedo-Marques PM de. Wia-Spine: a CBIR environment with embedded radiomic features to assess fragility fractures [Internet]. Proceedings. 2022 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS55023.2022.00020
Vancouver
Bêdo MVN, Ramos J da S, Traina AJM, Traina Junior C, Nogueira-Barbosa MH, Azevedo-Marques PM de. Wia-Spine: a CBIR environment with embedded radiomic features to assess fragility fractures [Internet]. Proceedings. 2022 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS55023.2022.00020
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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RAMOS, Jonathan da Silva et al. Analysis of vertebrae without fracture on spine MRI to assess bone fragility: a comparison of traditional machine learning and deep learning. 2022, Anais.. Los Alamitos: IEEE, 2022. Disponível em: https://doi.org/10.1109/CBMS55023.2022.00021. Acesso em: 03 maio 2024.
APA
Ramos, J. da S., Aguiar, E. J. de, Belizario, I. V., Costa, M. V. L., Maciel, J. G., Cazzolato, M. T., et al. (2022). Analysis of vertebrae without fracture on spine MRI to assess bone fragility: a comparison of traditional machine learning and deep learning. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS55023.2022.00021
NLM
Ramos J da S, Aguiar EJ de, Belizario IV, Costa MVL, Maciel JG, Cazzolato MT, Traina Junior C, Nogueira-Barbosa MH, Traina AJM. Analysis of vertebrae without fracture on spine MRI to assess bone fragility: a comparison of traditional machine learning and deep learning [Internet]. Proceedings. 2022 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS55023.2022.00021
Vancouver
Ramos J da S, Aguiar EJ de, Belizario IV, Costa MVL, Maciel JG, Cazzolato MT, Traina Junior C, Nogueira-Barbosa MH, Traina AJM. Analysis of vertebrae without fracture on spine MRI to assess bone fragility: a comparison of traditional machine learning and deep learning [Internet]. Proceedings. 2022 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS55023.2022.00021
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CAZZOLATO, Mirela Teixeira et al. TgraphSpot: fast and effective anomaly detection for time-evolving graphs. 2022, Anais.. Piscataway: IEEE, 2022. Disponível em: https://doi.org/10.1109/BigData55660.2022.10020898. Acesso em: 03 maio 2024.
APA
Cazzolato, M. T., Vijayakumar, S., Zheng, X., Park, N., Lee, M. -C., Fidalgo, P., et al. (2022). TgraphSpot: fast and effective anomaly detection for time-evolving graphs. In Proceedings. Piscataway: IEEE. doi:10.1109/BigData55660.2022.10020898
NLM
Cazzolato MT, Vijayakumar S, Zheng X, Park N, Lee M-C, Fidalgo P, Lages B, Traina AJM, Faloutsos C. TgraphSpot: fast and effective anomaly detection for time-evolving graphs [Internet]. Proceedings. 2022 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/BigData55660.2022.10020898
Vancouver
Cazzolato MT, Vijayakumar S, Zheng X, Park N, Lee M-C, Fidalgo P, Lages B, Traina AJM, Faloutsos C. TgraphSpot: fast and effective anomaly detection for time-evolving graphs [Internet]. Proceedings. 2022 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/BigData55660.2022.10020898
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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RAMOS, Jonathan da Silva et al. BEAUT: a radiomic approach to identify potential lumbar fractures in magnetic resonance imaging. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/CBMS52027.2021.00089. Acesso em: 03 maio 2024.
APA
Ramos, J. da S., Maciel, J. G., Cazzolato, M. T., Traina Junior, C., Nogueira-Barbosa, M. H., & Traina, A. J. M. (2021). BEAUT: a radiomic approach to identify potential lumbar fractures in magnetic resonance imaging. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS52027.2021.00089
NLM
Ramos J da S, Maciel JG, Cazzolato MT, Traina Junior C, Nogueira-Barbosa MH, Traina AJM. BEAUT: a radiomic approach to identify potential lumbar fractures in magnetic resonance imaging [Internet]. Proceedings. 2021 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00089
Vancouver
Ramos J da S, Maciel JG, Cazzolato MT, Traina Junior C, Nogueira-Barbosa MH, Traina AJM. BEAUT: a radiomic approach to identify potential lumbar fractures in magnetic resonance imaging [Internet]. Proceedings. 2021 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00089
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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CLEMENTINO JR, José Maria et al. Multilevel clustering explainer: an explainable approach to electronic health records. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/CBMS52027.2021.00073. Acesso em: 03 maio 2024.
APA
Clementino Jr, J. M., Faiçal, B. S., Bones, C. C., Traina Junior, C., Gutierrez, M. A., & Traina, A. J. M. (2021). Multilevel clustering explainer: an explainable approach to electronic health records. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS52027.2021.00073
NLM
Clementino Jr JM, Faiçal BS, Bones CC, Traina Junior C, Gutierrez MA, Traina AJM. Multilevel clustering explainer: an explainable approach to electronic health records [Internet]. Proceedings. 2021 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00073
Vancouver
Clementino Jr JM, Faiçal BS, Bones CC, Traina Junior C, Gutierrez MA, Traina AJM. Multilevel clustering explainer: an explainable approach to electronic health records [Internet]. Proceedings. 2021 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00073
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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LINHARES, Claudio Douglas Gouveia et al. I-CovidVis: a visual analytics tool for interoperable healthcare databases using graphs. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/CBMS52027.2021.00059. Acesso em: 03 maio 2024.
APA
Linhares, C. D. G., Lima, D. M. de, Bones, C. C., Rebelo, M. F. S., Gutierrez, M. A., Traina Junior, C., & Traina, A. J. M. (2021). I-CovidVis: a visual analytics tool for interoperable healthcare databases using graphs. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS52027.2021.00059
NLM
Linhares CDG, Lima DM de, Bones CC, Rebelo MFS, Gutierrez MA, Traina Junior C, Traina AJM. I-CovidVis: a visual analytics tool for interoperable healthcare databases using graphs [Internet]. Proceedings. 2021 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00059
Vancouver
Linhares CDG, Lima DM de, Bones CC, Rebelo MFS, Gutierrez MA, Traina Junior C, Traina AJM. I-CovidVis: a visual analytics tool for interoperable healthcare databases using graphs [Internet]. Proceedings. 2021 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00059
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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CLEMENTINO JR, José Maria et al. Bag-of-attributes representation: a vector space model for electronic health records analysis in OMOP. 2020, Anais.. Los Alamitos: IEEE, 2020. Disponível em: https://doi.org/10.1109/CBMS49503.2020.00045. Acesso em: 03 maio 2024.
APA
Clementino Jr, J. M., Bones, C. C., Faiçal, B. S., Linares, O. A. C., Lima, D. M. de, Gutierrez, M. A., et al. (2020). Bag-of-attributes representation: a vector space model for electronic health records analysis in OMOP. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS49503.2020.00045
NLM
Clementino Jr JM, Bones CC, Faiçal BS, Linares OAC, Lima DM de, Gutierrez MA, Traina Junior C, Traina AJM. Bag-of-attributes representation: a vector space model for electronic health records analysis in OMOP [Internet]. Proceedings. 2020 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00045
Vancouver
Clementino Jr JM, Bones CC, Faiçal BS, Linares OAC, Lima DM de, Gutierrez MA, Traina Junior C, Traina AJM. Bag-of-attributes representation: a vector space model for electronic health records analysis in OMOP [Internet]. Proceedings. 2020 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00045
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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LINARES, Oscar Alonso Cuadros et al. Efficient segmentation of cell nuclei in histopathological images. 2020, Anais.. Los Alamitos: IEEE, 2020. Disponível em: https://doi.org/10.1109/CBMS49503.2020.00017. Acesso em: 03 maio 2024.
APA
Linares, O. A. C., Soriano-Vargas, A., Faiçal, B. S., Hamann, B., Fabro, A. T., & Traina, A. J. M. (2020). Efficient segmentation of cell nuclei in histopathological images. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS49503.2020.00017
NLM
Linares OAC, Soriano-Vargas A, Faiçal BS, Hamann B, Fabro AT, Traina AJM. Efficient segmentation of cell nuclei in histopathological images [Internet]. Proceedings. 2020 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00017
Vancouver
Linares OAC, Soriano-Vargas A, Faiçal BS, Hamann B, Fabro AT, Traina AJM. Efficient segmentation of cell nuclei in histopathological images [Internet]. Proceedings. 2020 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00017
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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CAZZOLATO, Mirela Teixeira et al. Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine. 2020, Anais.. Los Alamitos: IEEE, 2020. Disponível em: https://doi.org/10.1109/CBMS49503.2020.00073. Acesso em: 03 maio 2024.
APA
Cazzolato, M. T., Ramos, J. da S., Rodrigues, L. S., Scabora, L. de C., Chino, D. Y. T., Jorge, A. E. S., et al. (2020). Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS49503.2020.00073
NLM
Cazzolato MT, Ramos J da S, Rodrigues LS, Scabora L de C, Chino DYT, Jorge AES, Azevedo-Marques PM de, Traina Junior C, Traina AJM. Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine [Internet]. Proceedings. 2020 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00073
Vancouver
Cazzolato MT, Ramos J da S, Rodrigues LS, Scabora L de C, Chino DYT, Jorge AES, Azevedo-Marques PM de, Traina Junior C, Traina AJM. Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine [Internet]. Proceedings. 2020 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00073
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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SILVA, Wellington S et al. A two-phase learning approach for the segmentation of dermatological wounds. 2019, Anais.. Los Alamitos: IEEE, 2019. Disponível em: https://doi.org/10.1109/CBMS.2019.00076. Acesso em: 03 maio 2024.
APA
Silva, W. S., Jasbick, D. L., Wilson, R. E., Azevedo-Marques, P. M. de, Traina, A. J. M., Santos, L. F. D., et al. (2019). A two-phase learning approach for the segmentation of dermatological wounds. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2019.00076
NLM
Silva WS, Jasbick DL, Wilson RE, Azevedo-Marques PM de, Traina AJM, Santos LFD, Jorge AES, Oliveira D de, Bêdo MVN. A two-phase learning approach for the segmentation of dermatological wounds [Internet]. Proceedings. 2019 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS.2019.00076
Vancouver
Silva WS, Jasbick DL, Wilson RE, Azevedo-Marques PM de, Traina AJM, Santos LFD, Jorge AES, Oliveira D de, Bêdo MVN. A two-phase learning approach for the segmentation of dermatological wounds [Internet]. Proceedings. 2019 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS.2019.00076
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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LINARES, Oscar Alonso Cuadros et al. How to automatically identify regions of interest in high-resolution images of lung biopsy for interstitial fibrosis diagnosis. 2019, Anais.. Los Alamitos: IEEE, 2019. Disponível em: https://doi.org/10.1109/CBMS.2019.00118. Acesso em: 03 maio 2024.
APA
Linares, O. A. C., Faiçal, B. S., Barbosa, P. R. C., Hamann, B., Fabro, A. T., & Traina, A. J. M. (2019). How to automatically identify regions of interest in high-resolution images of lung biopsy for interstitial fibrosis diagnosis. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2019.00118
NLM
Linares OAC, Faiçal BS, Barbosa PRC, Hamann B, Fabro AT, Traina AJM. How to automatically identify regions of interest in high-resolution images of lung biopsy for interstitial fibrosis diagnosis [Internet]. Proceedings. 2019 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS.2019.00118
Vancouver
Linares OAC, Faiçal BS, Barbosa PRC, Hamann B, Fabro AT, Traina AJM. How to automatically identify regions of interest in high-resolution images of lung biopsy for interstitial fibrosis diagnosis [Internet]. Proceedings. 2019 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS.2019.00118
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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RAMOS, Jonathan da Silva et al. 3DBGrowth: volumetric vertebrae segmentation and reconstruction in magnetic resonance imaging. 2019, Anais.. Los Alamitos: IEEE, 2019. Disponível em: https://doi.org/10.1109/CBMS.2019.00091. Acesso em: 03 maio 2024.
APA
Ramos, J. da S., Cazzolato, M. T., Faiçal, B. S., Nogueira-Barbosa, M. H., Traina Junior, C., & Traina, A. J. M. (2019). 3DBGrowth: volumetric vertebrae segmentation and reconstruction in magnetic resonance imaging. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2019.00091
NLM
Ramos J da S, Cazzolato MT, Faiçal BS, Nogueira-Barbosa MH, Traina Junior C, Traina AJM. 3DBGrowth: volumetric vertebrae segmentation and reconstruction in magnetic resonance imaging [Internet]. Proceedings. 2019 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS.2019.00091
Vancouver
Ramos J da S, Cazzolato MT, Faiçal BS, Nogueira-Barbosa MH, Traina Junior C, Traina AJM. 3DBGrowth: volumetric vertebrae segmentation and reconstruction in magnetic resonance imaging [Internet]. Proceedings. 2019 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS.2019.00091
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ZABOT, Guilherme Felipe et al. UCORM: indexing uncorrelated metric spaces for concise content-based retrieval of medical images. 2019, Anais.. Los Alamitos: IEEE, 2019. Disponível em: https://doi.org/10.1109/CBMS.2019.00070. Acesso em: 03 maio 2024.
APA
Zabot, G. F., Cazzolato, M. T., Scabora, L. de C., Faiçal, B. S., Traina, A. J. M., & Traina Junior, C. (2019). UCORM: indexing uncorrelated metric spaces for concise content-based retrieval of medical images. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2019.00070
NLM
Zabot GF, Cazzolato MT, Scabora L de C, Faiçal BS, Traina AJM, Traina Junior C. UCORM: indexing uncorrelated metric spaces for concise content-based retrieval of medical images [Internet]. Proceedings. 2019 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS.2019.00070
Vancouver
Zabot GF, Cazzolato MT, Scabora L de C, Faiçal BS, Traina AJM, Traina Junior C. UCORM: indexing uncorrelated metric spaces for concise content-based retrieval of medical images [Internet]. Proceedings. 2019 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/CBMS.2019.00070
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RAMOS, Jonathan S et al. Fast and smart segmentation of paraspinal muscles in magnetic resonance imaging with CleverSeg. 2019, Anais.. Los Alamitos: IEEE, 2019. Disponível em: https://doi.org/10.1109/SIBGRAPI.2019.00019. Acesso em: 03 maio 2024.
APA
Ramos, J. S., Cazzolato, M. T., Faiçal, B. S., Linares, O. A. C., Barbosa, M. H. N., Traina Junior, C., & Traina, A. J. M. (2019). Fast and smart segmentation of paraspinal muscles in magnetic resonance imaging with CleverSeg. In Proceedings. Los Alamitos: IEEE. doi:10.1109/SIBGRAPI.2019.00019
NLM
Ramos JS, Cazzolato MT, Faiçal BS, Linares OAC, Barbosa MHN, Traina Junior C, Traina AJM. Fast and smart segmentation of paraspinal muscles in magnetic resonance imaging with CleverSeg [Internet]. Proceedings. 2019 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/SIBGRAPI.2019.00019
Vancouver
Ramos JS, Cazzolato MT, Faiçal BS, Linares OAC, Barbosa MHN, Traina Junior C, Traina AJM. Fast and smart segmentation of paraspinal muscles in magnetic resonance imaging with CleverSeg [Internet]. Proceedings. 2019 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/SIBGRAPI.2019.00019
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ZABOT, Guilherme Felipe et al. Efficient indexing of multiple metric spaces with spectra. 2019, Anais.. Los Alamitos: IEEE, 2019. Disponível em: https://doi.org/10.1109/ISM46123.2019.00038. Acesso em: 03 maio 2024.
APA
Zabot, G. F., Cazzolato, M. T., Scabora, L. de C., Traina, A. J. M., & Traina Junior, C. (2019). Efficient indexing of multiple metric spaces with spectra. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ISM46123.2019.00038
NLM
Zabot GF, Cazzolato MT, Scabora L de C, Traina AJM, Traina Junior C. Efficient indexing of multiple metric spaces with spectra [Internet]. Proceedings. 2019 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/ISM46123.2019.00038
Vancouver
Zabot GF, Cazzolato MT, Scabora L de C, Traina AJM, Traina Junior C. Efficient indexing of multiple metric spaces with spectra [Internet]. Proceedings. 2019 ;[citado 2024 maio 03 ] Available from: https://doi.org/10.1109/ISM46123.2019.00038
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CHINO, Daniel Y. T et al. ICARUS: retrieving skin ulcer images through bag-of-signatures. 2018, Anais.. Los Alamitos: IEEE, 2018. Disponível em: https://doi.org/10.1109/CBMS.2018.00022. Acesso em: 03 maio 2024.
APA
Chino, D. Y. T., Scabora, L. C., Cazzolato, M. T., Jorge, A. E. S., Traina Junior, C., & Traina, A. J. M. (2018). ICARUS: retrieving skin ulcer images through bag-of-signatures. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2018.00022