ReP USP - Resultado da busca

Trabalho de evento
An algorithm to train unrestricted sequential discrete morphological neural networks (2024)
Marcondes, Diego ; Feldman, Mariana de Sousa ; Barrera, Junior
Source: Proceedings. Conference titles: International Conference on Discrete Geometry and Mathematical Morphology - DGMM. Unidade: IME
Subjects: PROCESSAMENTO DE IMAGENS, REDES NEURAIS
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ABNT
MARCONDES, Diego e FELDMAN, Mariana de Sousa e BARRERA, Junior. An algorithm to train unrestricted sequential discrete morphological neural networks. 2024, Anais.. Cham: Springer, 2024. Disponível em: https://doi.org/10.1007/978-3-031-57793-2_14. Acesso em: 10 nov. 2024.
APA
Marcondes, D., Feldman, M. de S., & Barrera, J. (2024). An algorithm to train unrestricted sequential discrete morphological neural networks. In Proceedings. Cham: Springer. doi:10.1007/978-3-031-57793-2_14
NLM
Marcondes D, Feldman M de S, Barrera J. An algorithm to train unrestricted sequential discrete morphological neural networks [Internet]. Proceedings. 2024 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/978-3-031-57793-2_14
Vancouver
Marcondes D, Feldman M de S, Barrera J. An algorithm to train unrestricted sequential discrete morphological neural networks [Internet]. Proceedings. 2024 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/978-3-031-57793-2_14
Trabalho de evento
The lattice overparametrization paradigm for the machine learning of lattice operators (2024)
Marcondes, Diego ; Barrera, Junior
Source: Proceedings. Conference titles: International Conference on Discrete Geometry and Mathematical Morphology - DGMM. Unidade: IME
Subjects: PROCESSAMENTO DE IMAGENS, APRENDIZADO COMPUTACIONAL, OPERADORES
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ABNT
MARCONDES, Diego e BARRERA, Junior. The lattice overparametrization paradigm for the machine learning of lattice operators. 2024, Anais.. Cham: Springer, 2024. Disponível em: https://doi.org/10.1007/978-3-031-57793-2_16. Acesso em: 10 nov. 2024.
APA
Marcondes, D., & Barrera, J. (2024). The lattice overparametrization paradigm for the machine learning of lattice operators. In Proceedings. Cham: Springer. doi:10.1007/978-3-031-57793-2_16
NLM
Marcondes D, Barrera J. The lattice overparametrization paradigm for the machine learning of lattice operators [Internet]. Proceedings. 2024 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/978-3-031-57793-2_16
Vancouver
Marcondes D, Barrera J. The lattice overparametrization paradigm for the machine learning of lattice operators [Internet]. Proceedings. 2024 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/978-3-031-57793-2_16
Trabalho de evento
RAPIDFlow: recurrent adaptable pyramids with iterative decoding for efficient optical flow estimation (2024)
Morimitsu, Henrique ; Zhu, Xiaobin ; César Júnior, Roberto Marcondes ; Ji, Xiangyang ; Yin, Xu-Cheng
Source: Proceedings. Conference titles: International Conference on Robotics and Automation - ICRA. Unidade: IME
Assunto: PROCESSAMENTO DE IMAGENS
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ABNT
MORIMITSU, Henrique et al. RAPIDFlow: recurrent adaptable pyramids with iterative decoding for efficient optical flow estimation. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/ICRA57147.2024.10610277. Acesso em: 10 nov. 2024.
APA
Morimitsu, H., Zhu, X., César Júnior, R. M., Ji, X., & Yin, X. -C. (2024). RAPIDFlow: recurrent adaptable pyramids with iterative decoding for efficient optical flow estimation. In Proceedings. Piscataway: IEEE. doi:10.1109/ICRA57147.2024.10610277
NLM
Morimitsu H, Zhu X, César Júnior RM, Ji X, Yin X-C. RAPIDFlow: recurrent adaptable pyramids with iterative decoding for efficient optical flow estimation [Internet]. Proceedings. 2024 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/ICRA57147.2024.10610277
Vancouver
Morimitsu H, Zhu X, César Júnior RM, Ji X, Yin X-C. RAPIDFlow: recurrent adaptable pyramids with iterative decoding for efficient optical flow estimation [Internet]. Proceedings. 2024 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/ICRA57147.2024.10610277
Trabalho de evento
Advancing thyroid pathologies detection with recurrent neural networks and micro-FTIR hyperspectral imaging (2023)
Baffa, Matheus de Freitas Oliveira; Bachmann, Luciano ; Zezell, Denise Maria; Pereira, Thiago Martini; Deserno, Thomas Martin; Felipe, Joaquim Cezar
Source: Proceedings. Conference titles: IEEE International Symposium on Computer-Based Medical Systems (CBMS). Unidade: FFCLRP
Subjects: NEOPLASIAS DA TIREOIDE, REDES NEURAIS, VISÃO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS
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ABNT
BAFFA, Matheus de Freitas Oliveira et al. Advancing thyroid pathologies detection with recurrent neural networks and micro-FTIR hyperspectral imaging. 2023, Anais.. Washington: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 2023. Disponível em: https://doi.org/10.1109/CBMS58004.2023.00288. Acesso em: 10 nov. 2024.
APA
Baffa, M. de F. O., Bachmann, L., Zezell, D. M., Pereira, T. M., Deserno, T. M., & Felipe, J. C. (2023). Advancing thyroid pathologies detection with recurrent neural networks and micro-FTIR hyperspectral imaging. In Proceedings. Washington: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. doi:10.1109/CBMS58004.2023.00288
NLM
Baffa M de FO, Bachmann L, Zezell DM, Pereira TM, Deserno TM, Felipe JC. Advancing thyroid pathologies detection with recurrent neural networks and micro-FTIR hyperspectral imaging [Internet]. Proceedings. 2023 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00288
Vancouver
Baffa M de FO, Bachmann L, Zezell DM, Pereira TM, Deserno TM, Felipe JC. Advancing thyroid pathologies detection with recurrent neural networks and micro-FTIR hyperspectral imaging [Internet]. Proceedings. 2023 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00288
Trabalho de evento
Assessing vulnerabilities of deep learning explainability in medical image analysis under adversarial settings (2023)
Aguiar, Erikson Júlio de ; Costa, Márcus Vinícius Lobo ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR COMPUTADOR
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ABNT
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: 10 nov. 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 nov. 10 ] 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 nov. 10 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00184
Trabalho de evento
Unsupervised image segmentation by oriented image foresting transform in layered graphs (2023)
Kleine, Felipe A. S ; Santos, Luiz Felipe Dolabela; Cappabianco, Fabio A. M ; Miranda, Paulo André Vechiatto de
Source: Proceedings. Conference titles: Conference on Graphics, Patterns and Images - SIBGRAPI. Unidade: IME
Assunto: PROCESSAMENTO DE IMAGENS
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ABNT
KLEINE, Felipe A. S et al. Unsupervised image segmentation by oriented image foresting transform in layered graphs. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/SIBGRAPI59091.2023.10347172. Acesso em: 10 nov. 2024.
APA
Kleine, F. A. S., Santos, L. F. D., Cappabianco, F. A. M., & Miranda, P. A. V. de. (2023). Unsupervised image segmentation by oriented image foresting transform in layered graphs. In Proceedings. Piscataway: IEEE. doi:10.1109/SIBGRAPI59091.2023.10347172
NLM
Kleine FAS, Santos LFD, Cappabianco FAM, Miranda PAV de. Unsupervised image segmentation by oriented image foresting transform in layered graphs [Internet]. Proceedings. 2023 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/SIBGRAPI59091.2023.10347172
Vancouver
Kleine FAS, Santos LFD, Cappabianco FAM, Miranda PAV de. Unsupervised image segmentation by oriented image foresting transform in layered graphs [Internet]. Proceedings. 2023 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/SIBGRAPI59091.2023.10347172
Trabalho de evento
Modeling and interpreting 6-D object pose estimation (2023)
Soler, Diego Pavan ; Hirata Júnior, Roberto ; Espadoto, Mateus
Source: Proceedings. Conference titles: International Conference on Image Processing - ICIP. Unidade: IME
Subjects: PROCESSAMENTO DE IMAGENS, REDES NEURAIS, APRENDIZAGEM PROFUNDA
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ABNT
SOLER, Diego Pavan e HIRATA JÚNIOR, Roberto e ESPADOTO, Mateus. Modeling and interpreting 6-D object pose estimation. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/ICIP49359.2023.10223067. Acesso em: 10 nov. 2024.
APA
Soler, D. P., Hirata Júnior, R., & Espadoto, M. (2023). Modeling and interpreting 6-D object pose estimation. In Proceedings. Piscataway: IEEE. doi:10.1109/ICIP49359.2023.10223067
NLM
Soler DP, Hirata Júnior R, Espadoto M. Modeling and interpreting 6-D object pose estimation [Internet]. Proceedings. 2023 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/ICIP49359.2023.10223067
Vancouver
Soler DP, Hirata Júnior R, Espadoto M. Modeling and interpreting 6-D object pose estimation [Internet]. Proceedings. 2023 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/ICIP49359.2023.10223067
Trabalho de evento
A deep learning-based radiomics approach for COVID-19 detection from CXR images using ensemble learning model (2023)
Costa, Márcus Vinícius Lobo ; Aguiar, Erikson Júlio de ; Rodrigues, Lucas Santiago ; Ramos, Jonathan da Silva ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR COMPUTADOR, TECNOLOGIAS DA SAÚDE, COVID-19
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ABNT
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: 10 nov. 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 nov. 10 ] 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 nov. 10 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00272
Trabalho de evento
Deep depth completion of low-cost sensor indoor RGB-D using Euclidean distance-based weighted loss and edge-aware refinement (2022)
Castro, Augusto Ribeiro ; Grassi Júnior, Valdir ; Ponti, Moacir Antonelli
Source: Proceedings. Conference titles: International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - VISIGRAPP. Unidades: EESC, ICMC
Subjects: APRENDIZADO COMPUTACIONAL, VISÃO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS, REDES NEURAIS
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ABNT
CASTRO, Augusto Ribeiro e GRASSI JÚNIOR, Valdir e PONTI, Moacir Antonelli. Deep depth completion of low-cost sensor indoor RGB-D using Euclidean distance-based weighted loss and edge-aware refinement. 2022, Anais.. Lisboa: SciTePress, 2022. Disponível em: https://doi.org/10.5220/0010915300003124. Acesso em: 10 nov. 2024.
APA
Castro, A. R., Grassi Júnior, V., & Ponti, M. A. (2022). Deep depth completion of low-cost sensor indoor RGB-D using Euclidean distance-based weighted loss and edge-aware refinement. In Proceedings. Lisboa: SciTePress. doi:10.5220/0010915300003124
NLM
Castro AR, Grassi Júnior V, Ponti MA. Deep depth completion of low-cost sensor indoor RGB-D using Euclidean distance-based weighted loss and edge-aware refinement [Internet]. Proceedings. 2022 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.5220/0010915300003124
Vancouver
Castro AR, Grassi Júnior V, Ponti MA. Deep depth completion of low-cost sensor indoor RGB-D using Euclidean distance-based weighted loss and edge-aware refinement [Internet]. Proceedings. 2022 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.5220/0010915300003124
Trabalho de evento
Domain generalization in medical image segmentation via meta-learners (2022)
Oliveira, Hugo ; César Júnior, Roberto Marcondes ; Gama, Pedro H. T ; Santos, Jefersson A. dos
Source: Proceedings. Conference titles: Brazilian Symposium on Computer Graphics and Image Processing - SIBGRAPI. Unidade: IME
Assunto: PROCESSAMENTO DE IMAGENS
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ABNT
OLIVEIRA, Hugo et al. Domain generalization in medical image segmentation via meta-learners. 2022, Anais.. Piscataway: IEEE, 2022. Disponível em: https://doi.org/10.1109/SIBGRAPI55357.2022.9991767. Acesso em: 10 nov. 2024.
APA
Oliveira, H., César Júnior, R. M., Gama, P. H. T., & Santos, J. A. dos. (2022). Domain generalization in medical image segmentation via meta-learners. In Proceedings. Piscataway: IEEE. doi:10.1109/SIBGRAPI55357.2022.9991767
NLM
Oliveira H, César Júnior RM, Gama PHT, Santos JA dos. Domain generalization in medical image segmentation via meta-learners [Internet]. Proceedings. 2022 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/SIBGRAPI55357.2022.9991767
Vancouver
Oliveira H, César Júnior RM, Gama PHT, Santos JA dos. Domain generalization in medical image segmentation via meta-learners [Internet]. Proceedings. 2022 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/SIBGRAPI55357.2022.9991767
Trabalho de evento
Automatic lung segmentation with seed generation and ROIFT algorithm for the creation of anatomical atlas (2022)
Choi, Jungeui ; Ueda, Edson Kenji ; Duran, Guilherme Cortez ; Miranda, Paulo André Vechiatto de ; Tsuzuki, Marcos de Sales Guerra
Source: Proceedings. Conference titles: International Conference on Geometry and Graphics - ICGG. Unidades: IME, EP
Subjects: ANATOMIA, COMPUTAÇÃO APLICADA, PROCESSAMENTO DE IMAGENS
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ABNT
CHOI, Jungeui et al. Automatic lung segmentation with seed generation and ROIFT algorithm for the creation of anatomical atlas. 2022, Anais.. Cham: Springer, 2022. Disponível em: https://doi.org/10.1007/978-3-031-13588-0_55. Acesso em: 10 nov. 2024.
APA
Choi, J., Ueda, E. K., Duran, G. C., Miranda, P. A. V. de, & Tsuzuki, M. de S. G. (2022). Automatic lung segmentation with seed generation and ROIFT algorithm for the creation of anatomical atlas. In Proceedings. Cham: Springer. doi:10.1007/978-3-031-13588-0_55
NLM
Choi J, Ueda EK, Duran GC, Miranda PAV de, Tsuzuki M de SG. Automatic lung segmentation with seed generation and ROIFT algorithm for the creation of anatomical atlas [Internet]. Proceedings. 2022 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/978-3-031-13588-0_55
Vancouver
Choi J, Ueda EK, Duran GC, Miranda PAV de, Tsuzuki M de SG. Automatic lung segmentation with seed generation and ROIFT algorithm for the creation of anatomical atlas [Internet]. Proceedings. 2022 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/978-3-031-13588-0_55
Trabalho de evento
Locating urban trees near electric wires using Google Street View Photos: a new dataset and a semi-supervised learning approach in the wild (2022)
Oliveira, Artur André Almeida de Macedo ; Wang, Zhangyang ; Hirata Júnior, Roberto
Source: Proceedings. Conference titles: IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops - CVPRW. Unidade: IME
Subjects: VISÃO COMPUTACIONAL, REDES NEURAIS, PROCESSAMENTO DE IMAGENS
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ABNT
OLIVEIRA, Artur André Almeida de Macedo e WANG, Zhangyang e HIRATA JÚNIOR, Roberto. Locating urban trees near electric wires using Google Street View Photos: a new dataset and a semi-supervised learning approach in the wild. 2022, Anais.. Piscataway: IEEE, 2022. Disponível em: https://doi.org/10.1109/CVPRW56347.2022.00474. Acesso em: 10 nov. 2024.
APA
Oliveira, A. A. A. de M., Wang, Z., & Hirata Júnior, R. (2022). Locating urban trees near electric wires using Google Street View Photos: a new dataset and a semi-supervised learning approach in the wild. In Proceedings. Piscataway: IEEE. doi:10.1109/CVPRW56347.2022.00474
NLM
Oliveira AAA de M, Wang Z, Hirata Júnior R. Locating urban trees near electric wires using Google Street View Photos: a new dataset and a semi-supervised learning approach in the wild [Internet]. Proceedings. 2022 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/CVPRW56347.2022.00474
Vancouver
Oliveira AAA de M, Wang Z, Hirata Júnior R. Locating urban trees near electric wires using Google Street View Photos: a new dataset and a semi-supervised learning approach in the wild [Internet]. Proceedings. 2022 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/CVPRW56347.2022.00474
Trabalho de evento
Image segmentation by relaxed deep extreme cut with connected extreme points (2021)
Oliveira, Débora Emili Costa; Demario, Caio Lopes; Miranda, Paulo André Vechiatto de
Source: Proceedings. Conference titles: International Conference on Discrete Geometry and Mathematical Morphology - DGMM. Unidade: IME
Assunto: PROCESSAMENTO DE IMAGENS
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ABNT
OLIVEIRA, Débora Emili Costa e DEMARIO, Caio Lopes e MIRANDA, Paulo André Vechiatto de. Image segmentation by relaxed deep extreme cut with connected extreme points. 2021, Anais.. Cham: Springer, 2021. Disponível em: https://doi.org/10.1007/978-3-030-76657-3_32. Acesso em: 10 nov. 2024.
APA
Oliveira, D. E. C., Demario, C. L., & Miranda, P. A. V. de. (2021). Image segmentation by relaxed deep extreme cut with connected extreme points. In Proceedings. Cham: Springer. doi:10.1007/978-3-030-76657-3_32
NLM
Oliveira DEC, Demario CL, Miranda PAV de. Image segmentation by relaxed deep extreme cut with connected extreme points [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/978-3-030-76657-3_32
Vancouver
Oliveira DEC, Demario CL, Miranda PAV de. Image segmentation by relaxed deep extreme cut with connected extreme points [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/978-3-030-76657-3_32
Trabalho de evento
Brain tumor classification on multi-modality MRI using radiomic features (2021)
Souza, Davidson Lucas de; Coelho, Alessandra Martins; Felipe, Joaquim Cezar ; Baffa, Matheus de Freitas Oliveira
Source: Proceedings. Conference titles: IEEE International Conference on Bioinformatics and Biomedicine - BIBM. Unidades: FFCLRP, BIOENGENHARIA
Subjects: NEOPLASIAS CEREBRAIS, IMAGEM DIGITAL, RESSONÂNCIA MAGNÉTICA, APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS
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ABNT
SOUZA, Davidson Lucas de et al. Brain tumor classification on multi-modality MRI using radiomic features. 2021, Anais.. Piscataway: IEEE, 2021. Disponível em: https://doi.org/10.1109/BIBM52615.2021.9669791. Acesso em: 10 nov. 2024.
APA
Souza, D. L. de, Coelho, A. M., Felipe, J. C., & Baffa, M. de F. O. (2021). Brain tumor classification on multi-modality MRI using radiomic features. In Proceedings. Piscataway: IEEE. doi:10.1109/BIBM52615.2021.9669791
NLM
Souza DL de, Coelho AM, Felipe JC, Baffa M de FO. Brain tumor classification on multi-modality MRI using radiomic features [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/BIBM52615.2021.9669791
Vancouver
Souza DL de, Coelho AM, Felipe JC, Baffa M de FO. Brain tumor classification on multi-modality MRI using radiomic features [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/BIBM52615.2021.9669791
Trabalho de evento
Self-supervised learning for astronomical image classification (2021)
Martinazzo, Ana Carolina Rodrigues Cavalcante; Espadoto, Mateus ; Hirata, Nina Sumiko Tomita
Source: Proceedings. Conference titles: International Conference on Pattern Recognition - ICPR. Unidade: IME
Subjects: PROCESSAMENTO DE IMAGENS, APRENDIZADO COMPUTACIONAL, ASTRONOMIA
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ABNT
MARTINAZZO, Ana Carolina Rodrigues Cavalcante e ESPADOTO, Mateus e HIRATA, Nina Sumiko Tomita. Self-supervised learning for astronomical image classification. 2021, Anais.. Piscataway: IEEE, 2021. Disponível em: https://doi.org/10.1109/ICPR48806.2021.9412911. Acesso em: 10 nov. 2024.
APA
Martinazzo, A. C. R. C., Espadoto, M., & Hirata, N. S. T. (2021). Self-supervised learning for astronomical image classification. In Proceedings. Piscataway: IEEE. doi:10.1109/ICPR48806.2021.9412911
NLM
Martinazzo ACRC, Espadoto M, Hirata NST. Self-supervised learning for astronomical image classification [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/ICPR48806.2021.9412911
Vancouver
Martinazzo ACRC, Espadoto M, Hirata NST. Self-supervised learning for astronomical image classification [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/ICPR48806.2021.9412911
Trabalho de evento
Hyperspectral imaging system for tissue classification in H&E-stained histological slides (2021)
Souza, Mateus Materlini; Carvalho, Felipe Alvarenga; Sverzut, Enzo; Requena, Michelle Barreto ; Garcia, Marlon Rodrigues ; Pratavieira, Sebastião
Source: Proceedings. Conference titles: SBFoton International Optics and Photonics Conference - IOPC. Unidades: IFSC, EESC
Subjects: FLUORESCÊNCIA, ESPECTROS, PROCESSAMENTO DE IMAGENS
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ABNT
SOUZA, Mateus Materlini et al. Hyperspectral imaging system for tissue classification in H&E-stained histological slides. 2021, Anais.. Piscataway: Institute of Electrical and Electronic Engineers - IEEE, 2021. Disponível em: https://doi.org/10.1109/SBFOTONIOPC50774.2021.9461972. Acesso em: 10 nov. 2024.
APA
Souza, M. M., Carvalho, F. A., Sverzut, E., Requena, M. B., Garcia, M. R., & Pratavieira, S. (2021). Hyperspectral imaging system for tissue classification in H&E-stained histological slides. In Proceedings. Piscataway: Institute of Electrical and Electronic Engineers - IEEE. doi:10.1109/SBFOTONIOPC50774.2021.9461972
NLM
Souza MM, Carvalho FA, Sverzut E, Requena MB, Garcia MR, Pratavieira S. Hyperspectral imaging system for tissue classification in H&E-stained histological slides [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/SBFOTONIOPC50774.2021.9461972
Vancouver
Souza MM, Carvalho FA, Sverzut E, Requena MB, Garcia MR, Pratavieira S. Hyperspectral imaging system for tissue classification in H&E-stained histological slides [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/SBFOTONIOPC50774.2021.9461972
Trabalho de evento
Towards interactive image segmentation by dynamic and iterative spanning forest (2021)
Borlido Barcelos, Isabela ; Belém, Felipe; Miranda, Paulo André Vechiatto de ; Falcão, Alexandre Xavier ; Patrocínio Júnior, Zenilton Kleber G. do ; Guimaraes, Silvio Jamil Ferzoli
Source: Proceedings. Conference titles: International Conference on Discrete Geometry and Mathematical Morphology - DGMM. Unidade: IME
Assunto: PROCESSAMENTO DE IMAGENS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BORLIDO BARCELOS, Isabela et al. Towards interactive image segmentation by dynamic and iterative spanning forest. 2021, Anais.. Cham: Springer, 2021. Disponível em: https://doi.org/10.1007/978-3-030-76657-3_25. Acesso em: 10 nov. 2024.
APA
Borlido Barcelos, I., Belém, F., Miranda, P. A. V. de, Falcão, A. X., Patrocínio Júnior, Z. K. G. do, & Guimaraes, S. J. F. (2021). Towards interactive image segmentation by dynamic and iterative spanning forest. In Proceedings. Cham: Springer. doi:10.1007/978-3-030-76657-3_25
NLM
Borlido Barcelos I, Belém F, Miranda PAV de, Falcão AX, Patrocínio Júnior ZKG do, Guimaraes SJF. Towards interactive image segmentation by dynamic and iterative spanning forest [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/978-3-030-76657-3_25
Vancouver
Borlido Barcelos I, Belém F, Miranda PAV de, Falcão AX, Patrocínio Júnior ZKG do, Guimaraes SJF. Towards interactive image segmentation by dynamic and iterative spanning forest [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/978-3-030-76657-3_25
Trabalho de evento
Automatic segmentation of posterior fossa structures in pediatric brain MRIs (2021)
Oliveira, Hugo ; Dias, Larissa de Oliveira Penteado ; Pimenta, José Luiz Maciel ; Ferraciolli, Suely Fazio ; Takahashi, Marcelo Straus ; Bloch, Isabelle ; César Júnior, Roberto Marcondes
Source: Proceedings. Conference titles: Conference on Graphics, Patterns and Images - SIBGRAPI. Unidades: IME, FM
Subjects: PROCESSAMENTO DE IMAGENS, APRENDIZAGEM PROFUNDA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA, Hugo et al. Automatic segmentation of posterior fossa structures in pediatric brain MRIs. 2021, Anais.. Piscataway: IEEE, 2021. Disponível em: https://doi.org/10.1109/SIBGRAPI54419.2021.00025. Acesso em: 10 nov. 2024.
APA
Oliveira, H., Dias, L. de O. P., Pimenta, J. L. M., Ferraciolli, S. F., Takahashi, M. S., Bloch, I., & César Júnior, R. M. (2021). Automatic segmentation of posterior fossa structures in pediatric brain MRIs. In Proceedings. Piscataway: IEEE. doi:10.1109/SIBGRAPI54419.2021.00025
NLM
Oliveira H, Dias L de OP, Pimenta JLM, Ferraciolli SF, Takahashi MS, Bloch I, César Júnior RM. Automatic segmentation of posterior fossa structures in pediatric brain MRIs [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00025
Vancouver
Oliveira H, Dias L de OP, Pimenta JLM, Ferraciolli SF, Takahashi MS, Bloch I, César Júnior RM. Automatic segmentation of posterior fossa structures in pediatric brain MRIs [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00025
Trabalho de evento-anais periodico
Improving vibro-acoustography images using 2D wavelet transform (2021)
Marció, Bruno Silva; Carneiro, Antonio Adilton Oliveira ; Braz, Guilherme de Araújo ; Flesch, Rodolfo C. C.
Source: Proceedings. Conference titles: IEEE UFFC Latin America Ultrasonics Symposium (LAUS). Unidade: FFCLRP
Subjects: IMAGEM DIGITAL, PROCESSAMENTO DE IMAGENS, VIBRAÇÃO DO SOM
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARCIÓ, Bruno Silva et al. Improving vibro-acoustography images using 2D wavelet transform. Proceedings. Gainesville: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1109/LAUS53676.2021.9639146. Acesso em: 10 nov. 2024. , 2021
APA
Marció, B. S., Carneiro, A. A. O., Braz, G. de A., & Flesch, R. C. C. (2021). Improving vibro-acoustography images using 2D wavelet transform. Proceedings. Gainesville: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. doi:10.1109/LAUS53676.2021.9639146
NLM
Marció BS, Carneiro AAO, Braz G de A, Flesch RCC. Improving vibro-acoustography images using 2D wavelet transform [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/LAUS53676.2021.9639146
Vancouver
Marció BS, Carneiro AAO, Braz G de A, Flesch RCC. Improving vibro-acoustography images using 2D wavelet transform [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/LAUS53676.2021.9639146
Trabalho de evento
Adaptive multiplane image generation from a single internet picture (2021)
Luvizon, Diogo C; Carvalho, Gustavo Sutter Pessurno de; Santos, Andreza A. dos; Conceição, Jhonatas S; Flores-Campana, Jose Luis ; Decker, Luis G. L; Souza, Marcos R; Pedrini, Hélio ; Joia, Antonio; Penatti, Otávio A. B
Source: Proceedings. Conference titles: IEEE Winter Conference on Applications of Computer Vision - WACV. Unidade: ICMC
Subjects: VISÃO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS, RENDERIZAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LUVIZON, Diogo C et al. Adaptive multiplane image generation from a single internet picture. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/WACV48630.2021.00260. Acesso em: 10 nov. 2024.
APA
Luvizon, D. C., Carvalho, G. S. P. de, Santos, A. A. dos, Conceição, J. S., Flores-Campana, J. L., Decker, L. G. L., et al. (2021). Adaptive multiplane image generation from a single internet picture. In Proceedings. Los Alamitos: IEEE. doi:10.1109/WACV48630.2021.00260
NLM
Luvizon DC, Carvalho GSP de, Santos AA dos, Conceição JS, Flores-Campana JL, Decker LGL, Souza MR, Pedrini H, Joia A, Penatti OAB. Adaptive multiplane image generation from a single internet picture [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/WACV48630.2021.00260
Vancouver
Luvizon DC, Carvalho GSP de, Santos AA dos, Conceição JS, Flores-Campana JL, Decker LGL, Souza MR, Pedrini H, Joia A, Penatti OAB. Adaptive multiplane image generation from a single internet picture [Internet]. Proceedings. 2021 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/WACV48630.2021.00260

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