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Artigo de periodico
The Quasar Catalogue for S-PLUS DR4 (QuCatS) and the estimation of photometric redshifts (2024)
Nakazono, Lilianne Mariko Izuti ; Valença, Raquel Ruiz ; Soares, G.; Izbicki, Rafael ; Ivezić, Željko ; Lima, Erik Vinívius Rodrigues De ; Hirata, Nina Sumiko Tomita ; Sodré Júnior, Laerte ; Overzier, Roderik ; Fernandes, Felipe de Almeida ; Schwarz, G. B. Oliveira ; Schoenell, William ; Kanaan, Antonio ; Ribeiro, T; Oliveira, C. Mendes de
Source: Monthly Notices of the Royal Astronomical Society. Unidades: IME, IAG
Subjects: QUASARES, GALÁXIAS, COMPUTAÇÃO APLICADA, FOTOMETRIA, PROBABILIDADE
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NAKAZONO, Lilianne Mariko Izuti et al. The Quasar Catalogue for S-PLUS DR4 (QuCatS) and the estimation of photometric redshifts. Monthly Notices of the Royal Astronomical Society, v. 531, n. 1, p. 327-339, 2024Tradução . . Disponível em: https://doi.org/10.1093/mnras/stae971. Acesso em: 04 jul. 2024.
APA
Nakazono, L. M. I., Valença, R. R., Soares, G., Izbicki, R., Ivezić, Ž., Lima, E. V. R. D., et al. (2024). The Quasar Catalogue for S-PLUS DR4 (QuCatS) and the estimation of photometric redshifts. Monthly Notices of the Royal Astronomical Society, 531( 1), 327-339. doi:10.1093/mnras/stae971
NLM
Nakazono LMI, Valença RR, Soares G, Izbicki R, Ivezić Ž, Lima EVRD, Hirata NST, Sodré Júnior L, Overzier R, Fernandes F de A, Schwarz GBO , Schoenell W, Kanaan A, Ribeiro T, Oliveira CM de. The Quasar Catalogue for S-PLUS DR4 (QuCatS) and the estimation of photometric redshifts [Internet]. Monthly Notices of the Royal Astronomical Society. 2024 ; 531( 1): 327-339.[citado 2024 jul. 04 ] Available from: https://doi.org/10.1093/mnras/stae971
Vancouver
Nakazono LMI, Valença RR, Soares G, Izbicki R, Ivezić Ž, Lima EVRD, Hirata NST, Sodré Júnior L, Overzier R, Fernandes F de A, Schwarz GBO , Schoenell W, Kanaan A, Ribeiro T, Oliveira CM de. The Quasar Catalogue for S-PLUS DR4 (QuCatS) and the estimation of photometric redshifts [Internet]. Monthly Notices of the Royal Astronomical Society. 2024 ; 531( 1): 327-339.[citado 2024 jul. 04 ] Available from: https://doi.org/10.1093/mnras/stae971
Trabalho de evento
Separating particles from plankton images (2023)
Hirata, Nina Sumiko Tomita ; Morimitsu, Alexandre ; Goulart, Antonio José Homsi
Source: Proceedings. Conference titles: International Conference on Pattern Recognition - ICPR. Unidade: IME
Subjects: APRENDIZAGEM PROFUNDA, RECONHECIMENTO DE IMAGEM, PLÂNCTON
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HIRATA, Nina Sumiko Tomita e MORIMITSU, Alexandre e GOULART, Antonio José Homsi. Separating particles from plankton images. 2023, Anais.. Cham: Springer, 2023. Disponível em: https://doi.org/10.1007/978-3-031-37731-0_33. Acesso em: 04 jul. 2024.
APA
Hirata, N. S. T., Morimitsu, A., & Goulart, A. J. H. (2023). Separating particles from plankton images. In Proceedings. Cham: Springer. doi:10.1007/978-3-031-37731-0_33
NLM
Hirata NST, Morimitsu A, Goulart AJH. Separating particles from plankton images [Internet]. Proceedings. 2023 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.1007/978-3-031-37731-0_33
Vancouver
Hirata NST, Morimitsu A, Goulart AJH. Separating particles from plankton images [Internet]. Proceedings. 2023 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.1007/978-3-031-37731-0_33
Artigo de periodico
Visualizing high-dimensional functions with dense maps (2023)
Espadoto, Mateus ; Rodrigues, Francisco Caio Maia ; Hirata, Nina Sumiko Tomita ; Telea, Alexandru Cristian
Source: SN Computer Science. Unidades: IME, ICMC
Subjects: APRENDIZADO COMPUTACIONAL, PESQUISA OPERACIONAL, REGRESSÃO, OTIMIZAÇÃO MATEMÁTICA
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ESPADOTO, Mateus et al. Visualizing high-dimensional functions with dense maps. SN Computer Science, v. 4, n. artigo 230, p. 1, 2023Tradução . . Disponível em: https://doi.org/10.1007/s42979-022-01664-2. Acesso em: 04 jul. 2024.
APA
Espadoto, M., Rodrigues, F. C. M., Hirata, N. S. T., & Telea, A. C. (2023). Visualizing high-dimensional functions with dense maps. SN Computer Science, 4( artigo 230), 1. doi:10.1007/s42979-022-01664-2
NLM
Espadoto M, Rodrigues FCM, Hirata NST, Telea AC. Visualizing high-dimensional functions with dense maps [Internet]. SN Computer Science. 2023 ; 4( artigo 230): 1.[citado 2024 jul. 04 ] Available from: https://doi.org/10.1007/s42979-022-01664-2
Vancouver
Espadoto M, Rodrigues FCM, Hirata NST, Telea AC. Visualizing high-dimensional functions with dense maps [Internet]. SN Computer Science. 2023 ; 4( artigo 230): 1.[citado 2024 jul. 04 ] Available from: https://doi.org/10.1007/s42979-022-01664-2
Artigo de periodico
The information of attribute uncertainties: what convolutional neural networks can learn about errors in input data (2023)
Rodrigues, Natália Villa Nova ; Abramo, L. Raul ; Hirata, Nina Sumiko Tomita
Source: Machine Learning: Science and Technology. Unidades: IF, IME
Subjects: APRENDIZADO COMPUTACIONAL, ANÁLISE DE DADOS, ESTATÍSTICA
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RODRIGUES, Natália Villa Nova e ABRAMO, L. Raul e HIRATA, Nina Sumiko Tomita. The information of attribute uncertainties: what convolutional neural networks can learn about errors in input data. Machine Learning: Science and Technology, v. 4, n. artigo 045019, p. 1-26, 2023Tradução . . Disponível em: https://doi.org/10.1088/2632-2153/ad0285. Acesso em: 04 jul. 2024.
APA
Rodrigues, N. V. N., Abramo, L. R., & Hirata, N. S. T. (2023). The information of attribute uncertainties: what convolutional neural networks can learn about errors in input data. Machine Learning: Science and Technology, 4( artigo 045019), 1-26. doi:10.1088/2632-2153/ad0285
NLM
Rodrigues NVN, Abramo LR, Hirata NST. The information of attribute uncertainties: what convolutional neural networks can learn about errors in input data [Internet]. Machine Learning: Science and Technology. 2023 ; 4( artigo 045019): 1-26.[citado 2024 jul. 04 ] Available from: https://doi.org/10.1088/2632-2153/ad0285
Vancouver
Rodrigues NVN, Abramo LR, Hirata NST. The information of attribute uncertainties: what convolutional neural networks can learn about errors in input data [Internet]. Machine Learning: Science and Technology. 2023 ; 4( artigo 045019): 1-26.[citado 2024 jul. 04 ] Available from: https://doi.org/10.1088/2632-2153/ad0285
Trabalho de evento
Spider species classification using vision transformers and convolutional neural networks (2023)
Magalhães, Arthur Teixeira ; Hirata, Nina Sumiko Tomita
Source: Anais estendidos. Conference titles: Conference on Graphics, Patterns and Images - SIBGRAPI. Unidade: IME
Subjects: REDES NEURAIS, VISÃO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS
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MAGALHÃES, Arthur Teixeira e HIRATA, Nina Sumiko Tomita. Spider species classification using vision transformers and convolutional neural networks. 2023, Anais.. Porto Alegre: SBC, 2023. Disponível em: https://doi.org/10.5753/sibgrapi.est.2023.27475. Acesso em: 04 jul. 2024.
APA
Magalhães, A. T., & Hirata, N. S. T. (2023). Spider species classification using vision transformers and convolutional neural networks. In Anais estendidos. Porto Alegre: SBC. doi:10.5753/sibgrapi.est.2023.27475
NLM
Magalhães AT, Hirata NST. Spider species classification using vision transformers and convolutional neural networks [Internet]. Anais estendidos. 2023 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.5753/sibgrapi.est.2023.27475
Vancouver
Magalhães AT, Hirata NST. Spider species classification using vision transformers and convolutional neural networks [Internet]. Anais estendidos. 2023 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.5753/sibgrapi.est.2023.27475
Trabalho de evento
Combining YOLO and visual rhythm for vehicle counting (2023)
Ribeiro, Victor Nascimento; Hirata, Nina Sumiko Tomita
Source: Anais estendidos. Conference titles: Conference on Graphics, Patterns and Images - SIBGRAPI. Unidades: IME, EP
Subjects: VISÃO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS
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RIBEIRO, Victor Nascimento e HIRATA, Nina Sumiko Tomita. Combining YOLO and visual rhythm for vehicle counting. 2023, Anais.. Porto Alegre: SBC, 2023. Disponível em: https://doi.org/10.5753/sibgrapi.est.2023.27473. Acesso em: 04 jul. 2024.
APA
Ribeiro, V. N., & Hirata, N. S. T. (2023). Combining YOLO and visual rhythm for vehicle counting. In Anais estendidos. Porto Alegre: SBC. doi:10.5753/sibgrapi.est.2023.27473
NLM
Ribeiro VN, Hirata NST. Combining YOLO and visual rhythm for vehicle counting [Internet]. Anais estendidos. 2023 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.5753/sibgrapi.est.2023.27473
Vancouver
Ribeiro VN, Hirata NST. Combining YOLO and visual rhythm for vehicle counting [Internet]. Anais estendidos. 2023 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.5753/sibgrapi.est.2023.27473
Trabalho de evento
Improving self-supervised dimensionality reduction: exploring hyperparameters and pseudo-labeling strategies (2023)
Oliveira, Artur André Almeida de Macedo ; Espadoto, Mateus ; Hirata Júnior, Roberto ; Hirata, Nina Sumiko Tomita ; Telea, Alexandru Cristian
Source: Proceedings. Conference titles: International Joint Conference on Computer Vision, Imaging and Computer Graphics - VISIGRAPP. Unidade: IME
Subjects: APRENDIZAGEM PROFUNDA, REDES NEURAIS
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OLIVEIRA, Artur André Almeida de Macedo et al. Improving self-supervised dimensionality reduction: exploring hyperparameters and pseudo-labeling strategies. 2023, Anais.. Cham: Springer, 2023. Disponível em: https://doi.org/10.1007/978-3-031-25477-2_7. Acesso em: 04 jul. 2024.
APA
Oliveira, A. A. A. de M., Espadoto, M., Hirata Júnior, R., Hirata, N. S. T., & Telea, A. C. (2023). Improving self-supervised dimensionality reduction: exploring hyperparameters and pseudo-labeling strategies. In Proceedings. Cham: Springer. doi:10.1007/978-3-031-25477-2_7
NLM
Oliveira AAA de M, Espadoto M, Hirata Júnior R, Hirata NST, Telea AC. Improving self-supervised dimensionality reduction: exploring hyperparameters and pseudo-labeling strategies [Internet]. Proceedings. 2023 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.1007/978-3-031-25477-2_7
Vancouver
Oliveira AAA de M, Espadoto M, Hirata Júnior R, Hirata NST, Telea AC. Improving self-supervised dimensionality reduction: exploring hyperparameters and pseudo-labeling strategies [Internet]. Proceedings. 2023 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.1007/978-3-031-25477-2_7
Trabalho de evento
Understanding attention-based encoder-decoder networks: a case study with chess scoresheet recognition (2022)
Hayashi, Sergio Yuji; Hirata, Nina Sumiko Tomita
Source: Proceedings. Conference titles: International Conference on Pattern Recognition - ICPR. Unidade: IME
Subjects: RECONHECIMENTO DE IMAGEM, REDES NEURAIS, ENGENHARIA DE CONHECIMENTO
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HAYASHI, Sergio Yuji e HIRATA, Nina Sumiko Tomita. Understanding attention-based encoder-decoder networks: a case study with chess scoresheet recognition. 2022, Anais.. Piscataway: IEEE, 2022. Disponível em: https://doi.org/10.1109/ICPR56361.2022.9956133. Acesso em: 04 jul. 2024.
APA
Hayashi, S. Y., & Hirata, N. S. T. (2022). Understanding attention-based encoder-decoder networks: a case study with chess scoresheet recognition. In Proceedings. Piscataway: IEEE. doi:10.1109/ICPR56361.2022.9956133
NLM
Hayashi SY, Hirata NST. Understanding attention-based encoder-decoder networks: a case study with chess scoresheet recognition [Internet]. Proceedings. 2022 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.1109/ICPR56361.2022.9956133
Vancouver
Hayashi SY, Hirata NST. Understanding attention-based encoder-decoder networks: a case study with chess scoresheet recognition [Internet]. Proceedings. 2022 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.1109/ICPR56361.2022.9956133
Trabalho de evento
Improving deep learning projections by neighborhood analysis (2022)
Modrakowski, Terri S ; Espadoto, Mateus ; Falcão, Alexandre Xavier ; Hirata, Nina Sumiko Tomita ; Telea, Alexandru Cristian
Source: Proceedings. Conference titles: International Joint Conference on Computer Vision, Imaging and Computer Graphics - VISIGRAPP. Unidade: IME
Subjects: APRENDIZAGEM PROFUNDA, REDES NEURAIS
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MODRAKOWSKI, Terri S et al. Improving deep learning projections by neighborhood analysis. 2022, Anais.. Cham: Springer, 2022. Disponível em: https://doi.org/10.1007/978-3-030-94893-1_6. Acesso em: 04 jul. 2024.
APA
Modrakowski, T. S., Espadoto, M., Falcão, A. X., Hirata, N. S. T., & Telea, A. C. (2022). Improving deep learning projections by neighborhood analysis. In Proceedings. Cham: Springer. doi:10.1007/978-3-030-94893-1_6
NLM
Modrakowski TS, Espadoto M, Falcão AX, Hirata NST, Telea AC. Improving deep learning projections by neighborhood analysis [Internet]. Proceedings. 2022 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.1007/978-3-030-94893-1_6
Vancouver
Modrakowski TS, Espadoto M, Falcão AX, Hirata NST, Telea AC. Improving deep learning projections by neighborhood analysis [Internet]. Proceedings. 2022 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.1007/978-3-030-94893-1_6
Trabalho de evento
Deep learning and t-SNE projection for plankton images clusterization (2022)
Goulart, Antonio José Homsi; Morimitsu, Alexandre ; Jacomassi, Renan; Hirata, Nina Sumiko Tomita ; Lopes, Rubens Mendes
Source: Proceedings. Conference titles: Oceans Conference. Unidades: IME, IO
Subjects: APRENDIZAGEM PROFUNDA, ALGORITMOS PARA PROCESSAMENTO, PLÂNCTON, IMAGEM DIGITAL
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GOULART, Antonio José Homsi et al. Deep learning and t-SNE projection for plankton images clusterization. 2022, Anais.. Piscataway: IEEE, 2022. Disponível em: https://doi.org/10.23919/OCEANS44145.2021.9706043. Acesso em: 04 jul. 2024.
APA
Goulart, A. J. H., Morimitsu, A., Jacomassi, R., Hirata, N. S. T., & Lopes, R. M. (2022). Deep learning and t-SNE projection for plankton images clusterization. In Proceedings. Piscataway: IEEE. doi:10.23919/OCEANS44145.2021.9706043
NLM
Goulart AJH, Morimitsu A, Jacomassi R, Hirata NST, Lopes RM. Deep learning and t-SNE projection for plankton images clusterization [Internet]. Proceedings. 2022 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.23919/OCEANS44145.2021.9706043
Vancouver
Goulart AJH, Morimitsu A, Jacomassi R, Hirata NST, Lopes RM. Deep learning and t-SNE projection for plankton images clusterization [Internet]. Proceedings. 2022 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.23919/OCEANS44145.2021.9706043
Artigo de periodico
From mathematical morphology to machine learning of image operators (2022)
Barrera, Junior ; Hashimoto, Ronaldo Fumio ; Hirata, Nina Sumiko Tomita ; Hirata Júnior, Roberto ; Reis, Marcelo S.
Source: São Paulo Journal of Mathematical Sciences. Unidade: IME
Subjects: METODOLOGIA E TÉCNICAS DE COMPUTAÇÃO, PROCESSAMENTO DE IMAGENS
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BARRERA, Junior et al. From mathematical morphology to machine learning of image operators. São Paulo Journal of Mathematical Sciences, 2022Tradução . . Disponível em: https://doi.org/10.1007/s40863-022-00303-1. Acesso em: 04 jul. 2024.
APA
Barrera, J., Hashimoto, R. F., Hirata, N. S. T., Hirata Júnior, R., & Reis, M. S. (2022). From mathematical morphology to machine learning of image operators. São Paulo Journal of Mathematical Sciences. doi:10.1007/s40863-022-00303-1
NLM
Barrera J, Hashimoto RF, Hirata NST, Hirata Júnior R, Reis MS. From mathematical morphology to machine learning of image operators [Internet]. São Paulo Journal of Mathematical Sciences. 2022 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.1007/s40863-022-00303-1
Vancouver
Barrera J, Hashimoto RF, Hirata NST, Hirata Júnior R, Reis MS. From mathematical morphology to machine learning of image operators [Internet]. São Paulo Journal of Mathematical Sciences. 2022 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.1007/s40863-022-00303-1
Artigo de periodico
Digital signal analysis based on convolutional neural networks for active target time projection chambers (2022)
Fortino, Guilherme Ferrari ; Cardona, Juan Carlos Zamora ; Tamayose, Leonardo Eiji ; Hirata, Nina Sumiko Tomita ; Guimarães, Valdir
Source: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. Unidades: IME, IF
Subjects: REDES NEURAIS, PROCESSAMENTO DE SINAIS
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FORTINO, Guilherme Ferrari et al. Digital signal analysis based on convolutional neural networks for active target time projection chambers. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, v. 1031, n. artigo 166497, p. 1-7, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.nima.2022.166497. Acesso em: 04 jul. 2024.
APA
Fortino, G. F., Cardona, J. C. Z., Tamayose, L. E., Hirata, N. S. T., & Guimarães, V. (2022). Digital signal analysis based on convolutional neural networks for active target time projection chambers. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 1031( artigo 166497), 1-7. doi:10.1016/j.nima.2022.166497
NLM
Fortino GF, Cardona JCZ, Tamayose LE, Hirata NST, Guimarães V. Digital signal analysis based on convolutional neural networks for active target time projection chambers [Internet]. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2022 ; 1031( artigo 166497): 1-7.[citado 2024 jul. 04 ] Available from: https://doi.org/10.1016/j.nima.2022.166497
Vancouver
Fortino GF, Cardona JCZ, Tamayose LE, Hirata NST, Guimarães V. Digital signal analysis based on convolutional neural networks for active target time projection chambers [Internet]. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2022 ; 1031( artigo 166497): 1-7.[citado 2024 jul. 04 ] Available from: https://doi.org/10.1016/j.nima.2022.166497
Artigo de periodico
Toward a quantitative survey of dimension reduction techniques (2021)
Espadoto, Mateus ; Martins, Rafael M. ; Kerren, Andreas ; Hirata, Nina Sumiko Tomita ; Telea, Alexandru Cristian
Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: IME
Subjects: BENCHMARKING, APRENDIZADO COMPUTACIONAL, ESTRUTURAS DE DADOS
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ESPADOTO, Mateus et al. Toward a quantitative survey of dimension reduction techniques. IEEE Transactions on Visualization and Computer Graphics, v. 27, n. 3, p. 2153-2173, 2021Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2019.2944182. Acesso em: 04 jul. 2024.
APA
Espadoto, M., Martins, R. M., Kerren, A., Hirata, N. S. T., & Telea, A. C. (2021). Toward a quantitative survey of dimension reduction techniques. IEEE Transactions on Visualization and Computer Graphics, 27( 3), 2153-2173. doi:10.1109/TVCG.2019.2944182
NLM
Espadoto M, Martins RM, Kerren A, Hirata NST, Telea AC. Toward a quantitative survey of dimension reduction techniques [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 3): 2153-2173.[citado 2024 jul. 04 ] Available from: https://doi.org/10.1109/TVCG.2019.2944182
Vancouver
Espadoto M, Martins RM, Kerren A, Hirata NST, Telea AC. Toward a quantitative survey of dimension reduction techniques [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 3): 2153-2173.[citado 2024 jul. 04 ] Available from: https://doi.org/10.1109/TVCG.2019.2944182
Trabalho de evento
OptMap: using dense maps for visualizing multidimensional optimization problems (2021)
Espadoto, Mateus ; Rodrigues, Francisco Caio Maia ; Hirata, Nina Sumiko Tomita ; Telea, Alexandru Cristian
Source: Proceedings. Conference titles: International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - VISIGRAPP. Unidade: IME
Subjects: COMPUTAÇÃO GRÁFICA, VISÃO COMPUTACIONAL
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ABNT
ESPADOTO, Mateus et al. OptMap: using dense maps for visualizing multidimensional optimization problems. 2021, Anais.. Lisboa: SciTePress, 2021. Disponível em: https://doi.org/10.5220/0010288501230132. Acesso em: 04 jul. 2024.
APA
Espadoto, M., Rodrigues, F. C. M., Hirata, N. S. T., & Telea, A. C. (2021). OptMap: using dense maps for visualizing multidimensional optimization problems. In Proceedings. Lisboa: SciTePress. doi:10.5220/0010288501230132
NLM
Espadoto M, Rodrigues FCM, Hirata NST, Telea AC. OptMap: using dense maps for visualizing multidimensional optimization problems [Internet]. Proceedings. 2021 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.5220/0010288501230132
Vancouver
Espadoto M, Rodrigues FCM, Hirata NST, Telea AC. OptMap: using dense maps for visualizing multidimensional optimization problems [Internet]. Proceedings. 2021 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.5220/0010288501230132
Artigo de periodico
On machine-learning morphological image operators (2021)
Hirata, Nina Sumiko Tomita ; Papakostas, George A.
Source: Mathematics. Unidade: IME
Subjects: PROCESSAMENTO DE IMAGENS, APRENDIZAGEM PROFUNDA, FUNÇÕES BOOLEANAS
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HIRATA, Nina Sumiko Tomita e PAPAKOSTAS, George A. On machine-learning morphological image operators. Mathematics, v. 9, n. artigo 1854, p. 1-22, 2021Tradução . . Disponível em: https://doi.org/10.3390/math9161854. Acesso em: 04 jul. 2024.
APA
Hirata, N. S. T., & Papakostas, G. A. (2021). On machine-learning morphological image operators. Mathematics, 9( artigo 1854), 1-22. doi:10.3390/math9161854
NLM
Hirata NST, Papakostas GA. On machine-learning morphological image operators [Internet]. Mathematics. 2021 ; 9( artigo 1854): 1-22.[citado 2024 jul. 04 ] Available from: https://doi.org/10.3390/math9161854
Vancouver
Hirata NST, Papakostas GA. On machine-learning morphological image operators [Internet]. Mathematics. 2021 ; 9( artigo 1854): 1-22.[citado 2024 jul. 04 ] Available from: https://doi.org/10.3390/math9161854
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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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: 04 jul. 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 jul. 04 ] 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 jul. 04 ] Available from: https://doi.org/10.1109/ICPR48806.2021.9412911
Dissertação (Mestrado)
A self-supervised learning approach for astronomical images (2021)
Martinazzo, Ana Carolina Rodrigues Cavalcante; Hirata, Nina Sumiko Tomita (Orientador)
Unidade: IME
Subjects: PROCESSAMENTO DE IMAGENS, ASTRONOMIA, SOFTWARES, REDES NEURAIS, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTINAZZO, Ana Carolina Rodrigues Cavalcante. A self-supervised learning approach for astronomical images. 2021. Dissertação (Mestrado) – Universidade de São Paulo, São Paulo, 2021. Disponível em: https://www.teses.usp.br/teses/disponiveis/45/45134/tde-11012022-203357/. Acesso em: 04 jul. 2024.
APA
Martinazzo, A. C. R. C. (2021). A self-supervised learning approach for astronomical images (Dissertação (Mestrado). Universidade de São Paulo, São Paulo. Recuperado de https://www.teses.usp.br/teses/disponiveis/45/45134/tde-11012022-203357/
NLM
Martinazzo ACRC. A self-supervised learning approach for astronomical images [Internet]. 2021 ;[citado 2024 jul. 04 ] Available from: https://www.teses.usp.br/teses/disponiveis/45/45134/tde-11012022-203357/
Vancouver
Martinazzo ACRC. A self-supervised learning approach for astronomical images [Internet]. 2021 ;[citado 2024 jul. 04 ] Available from: https://www.teses.usp.br/teses/disponiveis/45/45134/tde-11012022-203357/
Trabalho de evento
Self-supervised dimensionality reduction with neural networks and pseudo-labeling (2021)
Espadoto, Mateus ; Hirata, Nina Sumiko Tomita ; Telea, Alexandru Cristian
Source: Proceedings. Conference titles: International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - VISIGRAPP. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ESPADOTO, Mateus e HIRATA, Nina Sumiko Tomita e TELEA, Alexandru Cristian. Self-supervised dimensionality reduction with neural networks and pseudo-labeling. 2021, Anais.. Lisboa: SciTePress, 2021. Disponível em: https://doi.org/10.5220/0010184800270037. Acesso em: 04 jul. 2024.
APA
Espadoto, M., Hirata, N. S. T., & Telea, A. C. (2021). Self-supervised dimensionality reduction with neural networks and pseudo-labeling. In Proceedings. Lisboa: SciTePress. doi:10.5220/0010184800270037
NLM
Espadoto M, Hirata NST, Telea AC. Self-supervised dimensionality reduction with neural networks and pseudo-labeling [Internet]. Proceedings. 2021 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.5220/0010184800270037
Vancouver
Espadoto M, Hirata NST, Telea AC. Self-supervised dimensionality reduction with neural networks and pseudo-labeling [Internet]. Proceedings. 2021 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.5220/0010184800270037
Trabalho de evento
Reducing the need for bounding box annotations in object detection using image classification data (2021)
Blanger, Leonardo ; Hirata, Nina Sumiko Tomita ; Jiang, Xiaoyi
Source: Proceedings. Conference titles: Brazilian Symposium on Computer Graphics and Image Processing - SIBGRAPI. Unidade: IME
Subjects: VISÃO COMPUTACIONAL, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE OBJETOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BLANGER, Leonardo e HIRATA, Nina Sumiko Tomita e JIANG, Xiaoyi. Reducing the need for bounding box annotations in object detection using image classification data. 2021, Anais.. Piscataway: IEEE, 2021. Disponível em: https://doi.org/10.1109/SIBGRAPI54419.2021.00035. Acesso em: 04 jul. 2024.
APA
Blanger, L., Hirata, N. S. T., & Jiang, X. (2021). Reducing the need for bounding box annotations in object detection using image classification data. In Proceedings. Piscataway: IEEE. doi:10.1109/SIBGRAPI54419.2021.00035
NLM
Blanger L, Hirata NST, Jiang X. Reducing the need for bounding box annotations in object detection using image classification data [Internet]. Proceedings. 2021 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00035
Vancouver
Blanger L, Hirata NST, Jiang X. Reducing the need for bounding box annotations in object detection using image classification data [Internet]. Proceedings. 2021 ;[citado 2024 jul. 04 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00035
Tese (Doutorado)
Learning multidimensional projections with neural networks (2021)
Espadoto, Mateus ; Hirata, Nina Sumiko Tomita (Orientador)
Unidade: IME
Assunto: REDES NEURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ESPADOTO, Mateus. Learning multidimensional projections with neural networks. 2021. Tese (Doutorado) – Universidade de São Paulo, São Paulo, 2021. Disponível em: https://www.teses.usp.br/teses/disponiveis/45/45134/tde-29082022-101314/. Acesso em: 04 jul. 2024.
APA
Espadoto, M. (2021). Learning multidimensional projections with neural networks (Tese (Doutorado). Universidade de São Paulo, São Paulo. Recuperado de https://www.teses.usp.br/teses/disponiveis/45/45134/tde-29082022-101314/
NLM
Espadoto M. Learning multidimensional projections with neural networks [Internet]. 2021 ;[citado 2024 jul. 04 ] Available from: https://www.teses.usp.br/teses/disponiveis/45/45134/tde-29082022-101314/
Vancouver
Espadoto M. Learning multidimensional projections with neural networks [Internet]. 2021 ;[citado 2024 jul. 04 ] Available from: https://www.teses.usp.br/teses/disponiveis/45/45134/tde-29082022-101314/

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