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Artigo de periodico
CPAP adherence assessment via gaussian mixture modeling of telemonitored apnea therapy (2022)
Rodrigues Junior, José Fernando ; Bailly, Sebastien ; Pepin, Jean-Louis ; Goeuriot, Lorraine ; Spadon, Gabriel ; Amer-Yahia, Sihem
Source: Applied Sciences. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS, TECNOLOGIAS DA SAÚDE, TRANSTORNOS DO SONO, APNEIA DO SONO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RODRIGUES JUNIOR, José Fernando et al. CPAP adherence assessment via gaussian mixture modeling of telemonitored apnea therapy. Applied Sciences, v. 12, n. 15, p. 1-17, 2022Tradução . . Disponível em: https://doi.org/10.3390/app12157618. Acesso em: 01 nov. 2024.
APA
Rodrigues Junior, J. F., Bailly, S., Pepin, J. -L., Goeuriot, L., Spadon, G., & Amer-Yahia, S. (2022). CPAP adherence assessment via gaussian mixture modeling of telemonitored apnea therapy. Applied Sciences, 12( 15), 1-17. doi:10.3390/app12157618
NLM
Rodrigues Junior JF, Bailly S, Pepin J-L, Goeuriot L, Spadon G, Amer-Yahia S. CPAP adherence assessment via gaussian mixture modeling of telemonitored apnea therapy [Internet]. Applied Sciences. 2022 ; 12( 15): 1-17.[citado 2024 nov. 01 ] Available from: https://doi.org/10.3390/app12157618
Vancouver
Rodrigues Junior JF, Bailly S, Pepin J-L, Goeuriot L, Spadon G, Amer-Yahia S. CPAP adherence assessment via gaussian mixture modeling of telemonitored apnea therapy [Internet]. Applied Sciences. 2022 ; 12( 15): 1-17.[citado 2024 nov. 01 ] Available from: https://doi.org/10.3390/app12157618
Artigo de periodico
DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage (2021)
Machado, Bruno Brandoli ; Spadon, Gabriel ; Esau, Travis ; Hennessy, Patrick ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Amer-Yahia, Sihem ; Rodrigues Junior, José Fernando
Source: Computers and Electronics in Agriculture. Unidade: ICMC
Subjects: COMPUTAÇÃO MÓVEL, PROCESSAMENTO DE IMAGENS, AGRICULTURA DE PRECISÃO, PESTICIDAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MACHADO, Bruno Brandoli et al. DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage. Computers and Electronics in Agriculture, v. 180, n. Ja 2021, p. 1-9, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2020.105906. Acesso em: 01 nov. 2024.
APA
Machado, B. B., Spadon, G., Esau, T., Hennessy, P., Carvalho, A. C. P. de L. F. de, Amer-Yahia, S., & Rodrigues Junior, J. F. (2021). DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage. Computers and Electronics in Agriculture, 180( Ja 2021), 1-9. doi:10.1016/j.compag.2020.105906
NLM
Machado BB, Spadon G, Esau T, Hennessy P, Carvalho ACP de LF de, Amer-Yahia S, Rodrigues Junior JF. DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage [Internet]. Computers and Electronics in Agriculture. 2021 ; 180( Ja 2021): 1-9.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.compag.2020.105906
Vancouver
Machado BB, Spadon G, Esau T, Hennessy P, Carvalho ACP de LF de, Amer-Yahia S, Rodrigues Junior JF. DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage [Internet]. Computers and Electronics in Agriculture. 2021 ; 180( Ja 2021): 1-9.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.compag.2020.105906
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: 01 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. 01 ] 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. 01 ] Available from: https://doi.org/10.1016/j.ins.2020.09.024
Artigo de periodico
DermaDL: advanced convolutional neural networks for computer-aided skin-lesion classification (2021)
Lima, Daniel Mário de ; Rodrigues Junior, José Fernando ; Machado, Bruno Brandoli ; Goeuriot, Lorraine ; Amer-Yahia, Sihem
Source: SN Computer Science. Unidade: ICMC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, NEOPLASIAS CUTÂNEAS, MELANOMA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LIMA, Daniel Mário de et al. DermaDL: advanced convolutional neural networks for computer-aided skin-lesion classification. SN Computer Science, v. 2, n. 4, p. 1-13, 2021Tradução . . Disponível em: https://doi.org/10.1007/s42979-021-00641-5. Acesso em: 01 nov. 2024.
APA
Lima, D. M. de, Rodrigues Junior, J. F., Machado, B. B., Goeuriot, L., & Amer-Yahia, S. (2021). DermaDL: advanced convolutional neural networks for computer-aided skin-lesion classification. SN Computer Science, 2( 4), 1-13. doi:10.1007/s42979-021-00641-5
NLM
Lima DM de, Rodrigues Junior JF, Machado BB, Goeuriot L, Amer-Yahia S. DermaDL: advanced convolutional neural networks for computer-aided skin-lesion classification [Internet]. SN Computer Science. 2021 ; 2( 4): 1-13.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1007/s42979-021-00641-5
Vancouver
Lima DM de, Rodrigues Junior JF, Machado BB, Goeuriot L, Amer-Yahia S. DermaDL: advanced convolutional neural networks for computer-aided skin-lesion classification [Internet]. SN Computer Science. 2021 ; 2( 4): 1-13.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1007/s42979-021-00641-5
Trabalho de evento
Lig-Doctor: real-world clinical prognosis using a bi-directional neural network (2020)
Rodrigues Junior, José Fernando ; Spadon, Gabriel ; Machado, Bruno Brandoli ; Amer-Yahia, Sihem
Source: Proceedings. Conference titles: IEEE International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, 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: real-world clinical prognosis using a bi-directional neural network. 2020, Anais.. Los Alamitos: IEEE, 2020. Disponível em: https://doi.org/10.1109/CBMS49503.2020.00113. Acesso em: 01 nov. 2024.
APA
Rodrigues Junior, J. F., Spadon, G., Machado, B. B., & Amer-Yahia, S. (2020). Lig-Doctor: real-world clinical prognosis using a bi-directional neural network. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS49503.2020.00113
NLM
Rodrigues Junior JF, Spadon G, Machado BB, Amer-Yahia S. Lig-Doctor: real-world clinical prognosis using a bi-directional neural network [Internet]. Proceedings. 2020 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00113
Vancouver
Rodrigues Junior JF, Spadon G, Machado BB, Amer-Yahia S. Lig-Doctor: real-world clinical prognosis using a bi-directional neural network [Internet]. Proceedings. 2020 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00113
Trabalho de evento
DermaDL: advanced convolutional neural networks for automated melanoma detection (2020)
Rodrigues Junior, José Fernando ; Machado, Bruno Brandoli ; Amer-Yahia, Sihem
Source: Proceedings. Conference titles: IEEE International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, NEOPLASIAS CUTÂNEAS, MELANOMA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RODRIGUES JUNIOR, José Fernando e MACHADO, Bruno Brandoli e AMER-YAHIA, Sihem. DermaDL: advanced convolutional neural networks for automated melanoma detection. 2020, Anais.. Los Alamitos: IEEE, 2020. Disponível em: https://doi.org/10.1109/CBMS49503.2020.00101. Acesso em: 01 nov. 2024.
APA
Rodrigues Junior, J. F., Machado, B. B., & Amer-Yahia, S. (2020). DermaDL: advanced convolutional neural networks for automated melanoma detection. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS49503.2020.00101
NLM
Rodrigues Junior JF, Machado BB, Amer-Yahia S. DermaDL: advanced convolutional neural networks for automated melanoma detection [Internet]. Proceedings. 2020 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00101
Vancouver
Rodrigues Junior JF, Machado BB, Amer-Yahia S. DermaDL: advanced convolutional neural networks for automated melanoma detection [Internet]. Proceedings. 2020 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00101

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