ReP USP - Resultado da busca

Artigo de periodico-carta/editorial
Design and development of robust and precision personalized medicine. [Opinion] (2024)
Goswami, Anamitra; Sil, Moumita; Ratnaparkhi, Prashant; Goswami, Arunava; Mukherjee, Nabanita; Polikarpov, Igor
Source: Current Science. Unidade: IFSC
Subjects: APRENDIZADO COMPUTACIONAL, AVALIAÇÃO DE TECNOLOGIAS DA SAÚDE
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ABNT
GOSWAMI, Anamitra et al. Design and development of robust and precision personalized medicine. [Opinion]. Current Science. Bangalore: Instituto de Física de São Carlos, Universidade de São Paulo. Disponível em: https://doi.org/10.1126/science.adm9218. Acesso em: 17 ago. 2024. , 2024
APA
Goswami, A., Sil, M., Ratnaparkhi, P., Goswami, A., Mukherjee, N., & Polikarpov, I. (2024). Design and development of robust and precision personalized medicine. [Opinion]. Current Science. Bangalore: Instituto de Física de São Carlos, Universidade de São Paulo. doi:10.1126/science.adm9218
NLM
Goswami A, Sil M, Ratnaparkhi P, Goswami A, Mukherjee N, Polikarpov I. Design and development of robust and precision personalized medicine. [Opinion] [Internet]. Current Science. 2024 ; 126( 1): 149-150.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1126/science.adm9218
Vancouver
Goswami A, Sil M, Ratnaparkhi P, Goswami A, Mukherjee N, Polikarpov I. Design and development of robust and precision personalized medicine. [Opinion] [Internet]. Current Science. 2024 ; 126( 1): 149-150.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1126/science.adm9218
Artigo de periodico
TENNER: intrusion detection models for industrial networks based on ensemble learning (2024)
Dalarmelina, Nicole do Vale ; Arora, Pallavi; Rocha Filho, Geraldo Pereira ; Meneguette, Rodolfo Ipolito ; Teixeira, Marcio Andrey
Source: Journal of Surveillance, Security and Safety. Unidade: ICMC
Subjects: INTERNET, APRENDIZADO COMPUTACIONAL, APRENDIZAGEM PROFUNDA, CLUSTERS
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ABNT
DALARMELINA, Nicole do Vale et al. TENNER: intrusion detection models for industrial networks based on ensemble learning. Journal of Surveillance, Security and Safety, v. 5, p. 80-94, 2024Tradução . . Disponível em: https://doi.org/10.20517/jsss.2023.51. Acesso em: 17 ago. 2024.
APA
Dalarmelina, N. do V., Arora, P., Rocha Filho, G. P., Meneguette, R. I., & Teixeira, M. A. (2024). TENNER: intrusion detection models for industrial networks based on ensemble learning. Journal of Surveillance, Security and Safety, 5, 80-94. doi:10.20517/jsss.2023.51
NLM
Dalarmelina N do V, Arora P, Rocha Filho GP, Meneguette RI, Teixeira MA. TENNER: intrusion detection models for industrial networks based on ensemble learning [Internet]. Journal of Surveillance, Security and Safety. 2024 ; 5 80-94.[citado 2024 ago. 17 ] Available from: https://doi.org/10.20517/jsss.2023.51
Vancouver
Dalarmelina N do V, Arora P, Rocha Filho GP, Meneguette RI, Teixeira MA. TENNER: intrusion detection models for industrial networks based on ensemble learning [Internet]. Journal of Surveillance, Security and Safety. 2024 ; 5 80-94.[citado 2024 ago. 17 ] Available from: https://doi.org/10.20517/jsss.2023.51
Parte de monografia/livro-apres/pref/posf
Machine learning for advanced functional materials. [Prefácio] (2023)
Joshi, Nirav Kumar Jitendrabhai ; Kushvaha, Vinod; Madhushri, Priyanka
Source: Machine learning for advanced functional materials. Unidade: IFSC
Subjects: APRENDIZADO COMPUTACIONAL, ELETROQUÍMICA, SENSOR, INTELIGÊNCIA ARTIFICIAL
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ABNT
JOSHI, Nirav Kumar Jitendrabhai e KUSHVAHA, Vinod e MADHUSHRI, Priyanka. Machine learning for advanced functional materials. [Prefácio]. Machine learning for advanced functional materials. Singapore: Springer. Disponível em: https://doi.org/10.1007/978-981-99-0393-1. Acesso em: 17 ago. 2024. , 2023
APA
Joshi, N. K. J., Kushvaha, V., & Madhushri, P. (2023). Machine learning for advanced functional materials. [Prefácio]. Machine learning for advanced functional materials. Singapore: Springer. doi:10.1007/978-981-99-0393-1
NLM
Joshi NKJ, Kushvaha V, Madhushri P. Machine learning for advanced functional materials. [Prefácio] [Internet]. Machine learning for advanced functional materials. 2023 ;[citado 2024 ago. 17 ] Available from: https://doi.org/10.1007/978-981-99-0393-1
Vancouver
Joshi NKJ, Kushvaha V, Madhushri P. Machine learning for advanced functional materials. [Prefácio] [Internet]. Machine learning for advanced functional materials. 2023 ;[citado 2024 ago. 17 ] Available from: https://doi.org/10.1007/978-981-99-0393-1
Monografia/livro-ed/org
Machine learning for advanced functional materials (2023)
Joshi, Nirav Kumar Jitendrabhai (Editor) ; Kushvaha, Vinod (Editor); Madhushri, Priyanka (Editor)
Unidade: IFSC
Subjects: APRENDIZADO COMPUTACIONAL, ELETROQUÍMICA, SENSOR, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
Machine learning for advanced functional materials. . Singapore: Springer. Disponível em: https://doi.org/10.1007/978-981-99-0393-1. Acesso em: 17 ago. 2024. , 2023
APA
Machine learning for advanced functional materials. (2023). Machine learning for advanced functional materials. Singapore: Springer. doi:10.1007/978-981-99-0393-1
NLM
Machine learning for advanced functional materials [Internet]. 2023 ;[citado 2024 ago. 17 ] Available from: https://doi.org/10.1007/978-981-99-0393-1
Vancouver
Machine learning for advanced functional materials [Internet]. 2023 ;[citado 2024 ago. 17 ] Available from: https://doi.org/10.1007/978-981-99-0393-1
Artigo de periodico
Autonomous CNN (AutoCNN): a data-driven approach to network architecture determination (2022)
Aradhya, Abhay M. S ; Ashfahani, Andri; Angelina, Fienny; Pratama, Mahardhika ; Mello, Rodrigo Fernandes de ; Sundaram, Suresh
Source: Information Sciences. Unidade: ICMC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, COMPUTAÇÃO EVOLUTIVA
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ABNT
ARADHYA, Abhay M. S et al. Autonomous CNN (AutoCNN): a data-driven approach to network architecture determination. Information Sciences, v. 607, p. 638-653, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2022.05.100. Acesso em: 17 ago. 2024.
APA
Aradhya, A. M. S., Ashfahani, A., Angelina, F., Pratama, M., Mello, R. F. de, & Sundaram, S. (2022). Autonomous CNN (AutoCNN): a data-driven approach to network architecture determination. Information Sciences, 607, 638-653. doi:10.1016/j.ins.2022.05.100
NLM
Aradhya AMS, Ashfahani A, Angelina F, Pratama M, Mello RF de, Sundaram S. Autonomous CNN (AutoCNN): a data-driven approach to network architecture determination [Internet]. Information Sciences. 2022 ; 607 638-653.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.ins.2022.05.100
Vancouver
Aradhya AMS, Ashfahani A, Angelina F, Pratama M, Mello RF de, Sundaram S. Autonomous CNN (AutoCNN): a data-driven approach to network architecture determination [Internet]. Information Sciences. 2022 ; 607 638-653.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.ins.2022.05.100
Trabalho de evento
Multiview clustering on PPI network for gene selection and enrichment from microarray data (2014)
Swarnkar, Tripti; Simões, Sérgio Nery; Martins Júnior, David Correa; Anura, Anji; Brentani, Helena; Hashimoto, Ronaldo Fumio ; Mitra, Pabitra
Source: Proceedings. Conference titles: IEEE International Conference on Bioinformatics and Bioengineering - BIBE. Unidades: FM, IME
Subjects: BIOINFORMÁTICA, COMPUTAÇÃO APLICADA, APRENDIZADO COMPUTACIONAL, GENÉTICA
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ABNT
SWARNKAR, Tripti et al. Multiview clustering on PPI network for gene selection and enrichment from microarray data. 2014, Anais.. Los Alamitos: IEEE, 2014. Disponível em: https://doi.org/10.1109/BIBE.2014.33. Acesso em: 17 ago. 2024.
APA
Swarnkar, T., Simões, S. N., Martins Júnior, D. C., Anura, A., Brentani, H., Hashimoto, R. F., & Mitra, P. (2014). Multiview clustering on PPI network for gene selection and enrichment from microarray data. In Proceedings. Los Alamitos: IEEE. doi:10.1109/BIBE.2014.33
NLM
Swarnkar T, Simões SN, Martins Júnior DC, Anura A, Brentani H, Hashimoto RF, Mitra P. Multiview clustering on PPI network for gene selection and enrichment from microarray data [Internet]. Proceedings. 2014 ;[citado 2024 ago. 17 ] Available from: https://doi.org/10.1109/BIBE.2014.33
Vancouver
Swarnkar T, Simões SN, Martins Júnior DC, Anura A, Brentani H, Hashimoto RF, Mitra P. Multiview clustering on PPI network for gene selection and enrichment from microarray data [Internet]. Proceedings. 2014 ;[citado 2024 ago. 17 ] Available from: https://doi.org/10.1109/BIBE.2014.33

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