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Trabalho de evento
A metrics-oriented architectural model to characterize complexity on machine learning-enabled systems (2025)
Ferreira, Renato Cordeiro
Conference titles: IEEE/ACM International Conference on AI Engineering - Software Engineering for AI - CAIN. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, ARQUITETURA E ORGANIZAÇÃO DE COMPUTADORES, MÉTRICAS DE SOFTWARE
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ABNT
FERREIRA, Renato Cordeiro. A metrics-oriented architectural model to characterize complexity on machine learning-enabled systems. 2025, Anais.. Piscataway: IEEE, 2025. p. 256-260. Disponível em: https://doi.org/10.1109/CAIN66642.2025.00041. Acesso em: 08 out. 2025.
APA
Ferreira, R. C. (2025). A metrics-oriented architectural model to characterize complexity on machine learning-enabled systems. In (p. 256-260). Piscataway: IEEE. doi:10.1109/CAIN66642.2025.00041
NLM
Ferreira RC. A metrics-oriented architectural model to characterize complexity on machine learning-enabled systems [Internet]. 2025 ; 256-260.[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/CAIN66642.2025.00041
Vancouver
Ferreira RC. A metrics-oriented architectural model to characterize complexity on machine learning-enabled systems [Internet]. 2025 ; 256-260.[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/CAIN66642.2025.00041
Trabalho de evento
On the use of machine learning for modern IoT ELF malware detection (2025)
Souza, Cristian H.M. ; Batista, Daniel Macêdo
Source: Proceedings. Conference titles: IEEE Latin American Conference on Computational Intelligence - LA-CCI. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, GESTÃO DA SEGURANÇA EM SISTEMAS COMPUTACIONAIS
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ABNT
SOUZA, Cristian H.M. e BATISTA, Daniel Macêdo. On the use of machine learning for modern IoT ELF malware detection. 2025, Anais.. Piscataway: IEEE, 2025. p. 1-6. Disponível em: https://repositorio.usp.br/directbitstream/2b6f0605-3ca7-42af-ac9b-a9a8f1e8f68d/3272162_va.pdf. Acesso em: 08 out. 2025.
APA
Souza, C. H. M., & Batista, D. M. (2025). On the use of machine learning for modern IoT ELF malware detection. In Proceedings (p. 1-6). Piscataway: IEEE. Recuperado de https://repositorio.usp.br/directbitstream/2b6f0605-3ca7-42af-ac9b-a9a8f1e8f68d/3272162_va.pdf
NLM
Souza CHM, Batista DM. On the use of machine learning for modern IoT ELF malware detection [Internet]. Proceedings. 2025 ; 1-6.[citado 2025 out. 08 ] Available from: https://repositorio.usp.br/directbitstream/2b6f0605-3ca7-42af-ac9b-a9a8f1e8f68d/3272162_va.pdf
Vancouver
Souza CHM, Batista DM. On the use of machine learning for modern IoT ELF malware detection [Internet]. Proceedings. 2025 ; 1-6.[citado 2025 out. 08 ] Available from: https://repositorio.usp.br/directbitstream/2b6f0605-3ca7-42af-ac9b-a9a8f1e8f68d/3272162_va.pdf
Trabalho de evento
Grammar-based evolutionary approaches for software effort estimation (2025)
Basgalupp, Márcio Porto ; Barros, Rodrigo Coelho ; Cerri, Ricardo ; Neri, Ferrante ; Miranda, Péricles ; Ludermir, Teresa
Source: Proceedings. Conference titles: IEEE Congress on Evolutionary Computation - CEC. Unidade: ICMC
Subjects: ALGORITMOS GENÉTICOS, APRENDIZADO COMPUTACIONAL
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ABNT
BASGALUPP, Márcio Porto et al. Grammar-based evolutionary approaches for software effort estimation. 2025, Anais.. Piscataway: IEEE, 2025. Disponível em: https://doi.org/10.1109/CEC65147.2025.11042977. Acesso em: 08 out. 2025.
APA
Basgalupp, M. P., Barros, R. C., Cerri, R., Neri, F., Miranda, P., & Ludermir, T. (2025). Grammar-based evolutionary approaches for software effort estimation. In Proceedings. Piscataway: IEEE. doi:10.1109/CEC65147.2025.11042977
NLM
Basgalupp MP, Barros RC, Cerri R, Neri F, Miranda P, Ludermir T. Grammar-based evolutionary approaches for software effort estimation [Internet]. Proceedings. 2025 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/CEC65147.2025.11042977
Vancouver
Basgalupp MP, Barros RC, Cerri R, Neri F, Miranda P, Ludermir T. Grammar-based evolutionary approaches for software effort estimation [Internet]. Proceedings. 2025 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/CEC65147.2025.11042977
Trabalho de evento
ICU-TSB: a benchmark for temporal patient representation learning for unsupervised stratification into patient cohorts (2025)
Proios, Dimitrios ; Bornet, Alban ; Yazdani, Anthony ; Rodrigues Junior, José Fernando ; Teodoro, Douglas
Source: Proceedings. Conference titles: IEEE International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS, BENCHMARKS, SISTEMAS COMPUTADORIZADOS DE REGISTROS MÉDICOS, UNIDADES DE TERAPIA INTENSIVA
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ABNT
PROIOS, Dimitrios et al. ICU-TSB: a benchmark for temporal patient representation learning for unsupervised stratification into patient cohorts. 2025, Anais.. Los Alamitos: IEEE, 2025. Disponível em: https://doi.org/10.1109/CBMS65348.2025.00022. Acesso em: 08 out. 2025.
APA
Proios, D., Bornet, A., Yazdani, A., Rodrigues Junior, J. F., & Teodoro, D. (2025). ICU-TSB: a benchmark for temporal patient representation learning for unsupervised stratification into patient cohorts. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS65348.2025.00022
NLM
Proios D, Bornet A, Yazdani A, Rodrigues Junior JF, Teodoro D. ICU-TSB: a benchmark for temporal patient representation learning for unsupervised stratification into patient cohorts [Internet]. Proceedings. 2025 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/CBMS65348.2025.00022
Vancouver
Proios D, Bornet A, Yazdani A, Rodrigues Junior JF, Teodoro D. ICU-TSB: a benchmark for temporal patient representation learning for unsupervised stratification into patient cohorts [Internet]. Proceedings. 2025 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/CBMS65348.2025.00022
Trabalho de evento
AI-driven public health surveillance: analyzing vulnerable areas in Brazil using remote sensing and socioeconomic data (2025)
Silva, João Pedro da; Aguiar, Erikson Júlio de ; Spadon, Gabriel ; Traina, Agma Juci Machado ; Rodrigues Junior, José Fernando
Source: Proceedings. Conference titles: IEEE International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, SENSORIAMENTO REMOTO, INDICADORES SOCIOECONÔMICOS, SAÚDE PÚBLICA, BRASIL
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ABNT
SILVA, João Pedro da et al. AI-driven public health surveillance: analyzing vulnerable areas in Brazil using remote sensing and socioeconomic data. 2025, Anais.. Los Alamitos: IEEE, 2025. Disponível em: https://doi.org/10.1109/CBMS65348.2025.00180. Acesso em: 08 out. 2025.
APA
Silva, J. P. da, Aguiar, E. J. de, Spadon, G., Traina, A. J. M., & Rodrigues Junior, J. F. (2025). AI-driven public health surveillance: analyzing vulnerable areas in Brazil using remote sensing and socioeconomic data. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS65348.2025.00180
NLM
Silva JP da, Aguiar EJ de, Spadon G, Traina AJM, Rodrigues Junior JF. AI-driven public health surveillance: analyzing vulnerable areas in Brazil using remote sensing and socioeconomic data [Internet]. Proceedings. 2025 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/CBMS65348.2025.00180
Vancouver
Silva JP da, Aguiar EJ de, Spadon G, Traina AJM, Rodrigues Junior JF. AI-driven public health surveillance: analyzing vulnerable areas in Brazil using remote sensing and socioeconomic data [Internet]. Proceedings. 2025 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/CBMS65348.2025.00180
Trabalho de evento
Uncertainty quantification in measuring ore mass flow rate with data-driven soft sensors (2025)
Diniz, Francisco José dos Santos ; Matos, Saulo Neves ; Ueyama, Jó ; Marcolino, Leandro Soriano ; Luz, Eduardo José da Silva; Pessin, Gustavo
Source: Proceedings. Conference titles: IEEE International Instrumentation and Measurement Technology Conference. Unidade: ICMC
Subjects: EMPRESAS DE MINERAÇÃO, INDÚSTRIA 4.0, TOMADA DE DECISÃO, APRENDIZADO COMPUTACIONAL, PREDIÇÃO
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ABNT
DINIZ, Francisco José dos Santos et al. Uncertainty quantification in measuring ore mass flow rate with data-driven soft sensors. 2025, Anais.. Piscataway: IEEE, 2025. Disponível em: https://doi.org/10.1109/I2MTC62753.2025.11079114. Acesso em: 08 out. 2025.
APA
Diniz, F. J. dos S., Matos, S. N., Ueyama, J., Marcolino, L. S., Luz, E. J. da S., & Pessin, G. (2025). Uncertainty quantification in measuring ore mass flow rate with data-driven soft sensors. In Proceedings. Piscataway: IEEE. doi:10.1109/I2MTC62753.2025.11079114
NLM
Diniz FJ dos S, Matos SN, Ueyama J, Marcolino LS, Luz EJ da S, Pessin G. Uncertainty quantification in measuring ore mass flow rate with data-driven soft sensors [Internet]. Proceedings. 2025 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/I2MTC62753.2025.11079114
Vancouver
Diniz FJ dos S, Matos SN, Ueyama J, Marcolino LS, Luz EJ da S, Pessin G. Uncertainty quantification in measuring ore mass flow rate with data-driven soft sensors [Internet]. Proceedings. 2025 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/I2MTC62753.2025.11079114
Trabalho de evento
RadPleura: a radiomics-based framework for lung pleura classification in histology images from interstitial lung diseases (2024)
Linares, Oscar Alonso Cuadros ; Belizario, Ivar Vargas ; Batah, Sabrina Setembre ; Hamann, Bernd ; Fabro, Alexandre Todorovic ; Azevedo-Marques, Paulo Mazzoncini de ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: IEEE International Symposium on Biomedical Imaging - ISBI. Unidades: FMRP, ICMC
Subjects: RECONHECIMENTO DE IMAGEM, APRENDIZADO COMPUTACIONAL, DIAGNÓSTICO POR COMPUTADOR, DIAGNÓSTICO POR IMAGEM, DOENÇAS PULMONARES INTERSTICIAIS, PLEURA, TECNOLOGIAS DA SAÚDE
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ABNT
LINARES, Oscar Alonso Cuadros et al. RadPleura: a radiomics-based framework for lung pleura classification in histology images from interstitial lung diseases. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/ISBI56570.2024.10635328. Acesso em: 08 out. 2025.
APA
Linares, O. A. C., Belizario, I. V., Batah, S. S., Hamann, B., Fabro, A. T., Azevedo-Marques, P. M. de, & Traina, A. J. M. (2024). RadPleura: a radiomics-based framework for lung pleura classification in histology images from interstitial lung diseases. In Proceedings. Piscataway: IEEE. doi:10.1109/ISBI56570.2024.10635328
NLM
Linares OAC, Belizario IV, Batah SS, Hamann B, Fabro AT, Azevedo-Marques PM de, Traina AJM. RadPleura: a radiomics-based framework for lung pleura classification in histology images from interstitial lung diseases [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/ISBI56570.2024.10635328
Vancouver
Linares OAC, Belizario IV, Batah SS, Hamann B, Fabro AT, Azevedo-Marques PM de, Traina AJM. RadPleura: a radiomics-based framework for lung pleura classification in histology images from interstitial lung diseases [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/ISBI56570.2024.10635328
Trabalho de evento
iRisk: a scalable microservice for classifying issue risks based on crowdsourced App reviews (2024)
Lima, Vitor Mesaque Alves de ; Barbosa, Jacson Rodrigues ; Marcacini, Ricardo Marcondes
Source: Proceedings. Conference titles: IEEE International Conference on Software Maintenance and Evolution - ICSME. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS, PROCESSAMENTO DE LINGUAGEM NATURAL, RECONHECIMENTO DE TEXTO, ENGENHARIA DE SOFTWARE, APLICATIVOS MÓVEIS
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ABNT
LIMA, Vitor Mesaque Alves de e BARBOSA, Jacson Rodrigues e MARCACINI, Ricardo Marcondes. iRisk: a scalable microservice for classifying issue risks based on crowdsourced App reviews. 2024, Anais.. Los Alamitos: IEEE, 2024. Disponível em: https://doi.org/10.1109/ICSME58944.2024.00091. Acesso em: 08 out. 2025.
APA
Lima, V. M. A. de, Barbosa, J. R., & Marcacini, R. M. (2024). iRisk: a scalable microservice for classifying issue risks based on crowdsourced App reviews. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICSME58944.2024.00091
NLM
Lima VMA de, Barbosa JR, Marcacini RM. iRisk: a scalable microservice for classifying issue risks based on crowdsourced App reviews [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/ICSME58944.2024.00091
Vancouver
Lima VMA de, Barbosa JR, Marcacini RM. iRisk: a scalable microservice for classifying issue risks based on crowdsourced App reviews [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/ICSME58944.2024.00091
Trabalho de evento
Real-time intrusion detection with sequence-aware neural networks for Internet of medical things (2024)
Werneck, Heitor; Batista, Daniel Macêdo ; Hirata Júnior, Roberto ; Queiroz, Marcelo Gomes de
Source: Proceedings. Conference titles: Virtual Conference on Communications - VCC. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, INTERNET DAS COISAS, SAÚDE, REDES NEURAIS, GESTÃO DA SEGURANÇA EM SISTEMAS COMPUTACIONAIS
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ABNT
WERNECK, Heitor et al. Real-time intrusion detection with sequence-aware neural networks for Internet of medical things. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/VCC63113.2024.10914399. Acesso em: 08 out. 2025.
APA
Werneck, H., Batista, D. M., Hirata Júnior, R., & Queiroz, M. G. de. (2024). Real-time intrusion detection with sequence-aware neural networks for Internet of medical things. In Proceedings. Piscataway: IEEE. doi:10.1109/VCC63113.2024.10914399
NLM
Werneck H, Batista DM, Hirata Júnior R, Queiroz MG de. Real-time intrusion detection with sequence-aware neural networks for Internet of medical things [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/VCC63113.2024.10914399
Vancouver
Werneck H, Batista DM, Hirata Júnior R, Queiroz MG de. Real-time intrusion detection with sequence-aware neural networks for Internet of medical things [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/VCC63113.2024.10914399
Trabalho de evento
Unsupervised AutoML and dimensionality reduction for autonomous DDoS attack prediction (2024)
Neira, Anderson B.; Borges, Ligia F.; Batista, Daniel Macêdo ; Nogueira, Michele
Source: Proceedings. Conference titles: IEEE Latin-American Conference on Communications - LATINCOM. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, CRIME POR COMPUTADOR, SEGURANÇA DE REDES
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ABNT
NEIRA, Anderson B. et al. Unsupervised AutoML and dimensionality reduction for autonomous DDoS attack prediction. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/LATINCOM62985.2024.10770668. Acesso em: 08 out. 2025.
APA
Neira, A. B., Borges, L. F., Batista, D. M., & Nogueira, M. (2024). Unsupervised AutoML and dimensionality reduction for autonomous DDoS attack prediction. In Proceedings. Piscataway: IEEE. doi:10.1109/LATINCOM62985.2024.10770668
NLM
Neira AB, Borges LF, Batista DM, Nogueira M. Unsupervised AutoML and dimensionality reduction for autonomous DDoS attack prediction [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM62985.2024.10770668
Vancouver
Neira AB, Borges LF, Batista DM, Nogueira M. Unsupervised AutoML and dimensionality reduction for autonomous DDoS attack prediction [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM62985.2024.10770668
Trabalho de evento
Machine learning techniques for improving multiclass anomaly detection on conveyor belts (2024)
Matos, Saulo Neves ; Coletti, Otavio Ferracioli ; Zimmer, Rafael; Ugucioni Filho, Fernando; Carvalho, Ricardo C. C. L. de; Silva, Victor Rodrigues da; Franco, Jorge Luiz; Pinto, Thomas Vargas Barsante e ; Barros, Luiz Guilherme Dias de ; Ranieri, Caetano Mazzoni ; Lopes, Bruno Eduardo; Silva, Diego Furtado ; Ueyama, Jó ; Pessin, Gustavo
Source: Proceedings. Conference titles: IEEE International Instrumentation and Measurement Technology Conference - I2MTC. Unidades: ICMC, EESC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, MANUTENÇÃO PREDITIVA, TRANSPORTADORES DE CORREIA
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ABNT
MATOS, Saulo Neves et al. Machine learning techniques for improving multiclass anomaly detection on conveyor belts. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/I2MTC60896.2024.10561167. Acesso em: 08 out. 2025.
APA
Matos, S. N., Coletti, O. F., Zimmer, R., Ugucioni Filho, F., Carvalho, R. C. C. L. de, Silva, V. R. da, et al. (2024). Machine learning techniques for improving multiclass anomaly detection on conveyor belts. In Proceedings. Piscataway: IEEE. doi:10.1109/I2MTC60896.2024.10561167
NLM
Matos SN, Coletti OF, Zimmer R, Ugucioni Filho F, Carvalho RCCL de, Silva VR da, Franco JL, Pinto TVB e, Barros LGD de, Ranieri CM, Lopes BE, Silva DF, Ueyama J, Pessin G. Machine learning techniques for improving multiclass anomaly detection on conveyor belts [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/I2MTC60896.2024.10561167
Vancouver
Matos SN, Coletti OF, Zimmer R, Ugucioni Filho F, Carvalho RCCL de, Silva VR da, Franco JL, Pinto TVB e, Barros LGD de, Ranieri CM, Lopes BE, Silva DF, Ueyama J, Pessin G. Machine learning techniques for improving multiclass anomaly detection on conveyor belts [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/I2MTC60896.2024.10561167
Trabalho de evento
Framework for activity development in remote laboratories IEEE 1876–2019 standard based (2024)
Solis Lastra, Javier Ulises ; Brandão, Anarosa Alves Franco ; Albertini, Bruno de Carvalho
Source: ANDESCON. Conference titles: IEEE ANDESCON. Unidade: EP
Subjects: ENGENHARIA, APRENDIZADO COMPUTACIONAL, COLETA DE DADOS
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ABNT
SOLIS LASTRA, Javier Ulises e BRANDÃO, Anarosa Alves Franco e ALBERTINI, Bruno de Carvalho. Framework for activity development in remote laboratories IEEE 1876–2019 standard based. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: http://dx.doi.org/10.1109/ANDESCON61840.2024.10755789. Acesso em: 08 out. 2025.
APA
Solis Lastra, J. U., Brandão, A. A. F., & Albertini, B. de C. (2024). Framework for activity development in remote laboratories IEEE 1876–2019 standard based. In ANDESCON. Piscataway: IEEE. doi:10.1109/ANDESCON61840.2024.10755789
NLM
Solis Lastra JU, Brandão AAF, Albertini B de C. Framework for activity development in remote laboratories IEEE 1876–2019 standard based [Internet]. ANDESCON. 2024 ;[citado 2025 out. 08 ] Available from: http://dx.doi.org/10.1109/ANDESCON61840.2024.10755789
Vancouver
Solis Lastra JU, Brandão AAF, Albertini B de C. Framework for activity development in remote laboratories IEEE 1876–2019 standard based [Internet]. ANDESCON. 2024 ;[citado 2025 out. 08 ] Available from: http://dx.doi.org/10.1109/ANDESCON61840.2024.10755789
Trabalho de evento
Closing the loop: enhancing industrial productivity through soft sensor (2024)
Pereira, Paulo; Pinto, Thomas Vargas Barsante e ; Matos, Saulo Neves ; Barbosa, Higor; Pérez, José; Pessin, Gustavo
Source: Proceedings. Conference titles: IEEE International Instrumentation and Measurement Technology Conference - I2MTC. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, TRANSPORTADORES DE CORREIA, PRODUÇÃO MINERAL, INDÚSTRIA 4.0, CONTROLE DE PROCESSOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PEREIRA, Paulo et al. Closing the loop: enhancing industrial productivity through soft sensor. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/I2MTC60896.2024.10560702. Acesso em: 08 out. 2025.
APA
Pereira, P., Pinto, T. V. B. e, Matos, S. N., Barbosa, H., Pérez, J., & Pessin, G. (2024). Closing the loop: enhancing industrial productivity through soft sensor. In Proceedings. Piscataway: IEEE. doi:10.1109/I2MTC60896.2024.10560702
NLM
Pereira P, Pinto TVB e, Matos SN, Barbosa H, Pérez J, Pessin G. Closing the loop: enhancing industrial productivity through soft sensor [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/I2MTC60896.2024.10560702
Vancouver
Pereira P, Pinto TVB e, Matos SN, Barbosa H, Pérez J, Pessin G. Closing the loop: enhancing industrial productivity through soft sensor [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/I2MTC60896.2024.10560702
Trabalho de evento
Classification of LTR retrotransposons via interaction prediction (2024)
Cardoso, Silvana C. S; Domingues, Douglas Silva ; Paschoal, Alexandre Rossi ; Fischer, Carlos Norberto ; Cerri, Ricardo
Source: Proceedings. Conference titles: IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology - CIBCB. Unidades: ESALQ, ICMC
Subjects: BIOINFORMÁTICA, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CARDOSO, Silvana C. S et al. Classification of LTR retrotransposons via interaction prediction. 2024, Anais.. Los Alamitos: IEEE, 2024. Disponível em: https://doi.org/10.1109/CIBCB58642.2024.10702140. Acesso em: 08 out. 2025.
APA
Cardoso, S. C. S., Domingues, D. S., Paschoal, A. R., Fischer, C. N., & Cerri, R. (2024). Classification of LTR retrotransposons via interaction prediction. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CIBCB58642.2024.10702140
NLM
Cardoso SCS, Domingues DS, Paschoal AR, Fischer CN, Cerri R. Classification of LTR retrotransposons via interaction prediction [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/CIBCB58642.2024.10702140
Vancouver
Cardoso SCS, Domingues DS, Paschoal AR, Fischer CN, Cerri R. Classification of LTR retrotransposons via interaction prediction [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/CIBCB58642.2024.10702140
Trabalho de evento
Supervised models for detecting GPS attacks and faults in UAVs: a comparative analysis (2024)
Ferrão, Isadora Garcia ; Oliveira, André de; Marçal, Vitor ; Allão, Daniel; Espes, David ; Dezan, Catherine ; Branco, Kalinka Regina Lucas Jaquie Castelo
Source: Proceedings. Conference titles: Latin American Robotics Symposium - LARS. Unidades: ICMC, EESC
Subjects: AERONAVES NÃO TRIPULADAS, TOMADA DE DECISÃO, APRENDIZADO COMPUTACIONAL
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ABNT
FERRÃO, Isadora Garcia et al. Supervised models for detecting GPS attacks and faults in UAVs: a comparative analysis. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/LARS64411.2024.10786404. Acesso em: 08 out. 2025.
APA
Ferrão, I. G., Oliveira, A. de, Marçal, V., Allão, D., Espes, D., Dezan, C., & Branco, K. R. L. J. C. (2024). Supervised models for detecting GPS attacks and faults in UAVs: a comparative analysis. In Proceedings. Piscataway: IEEE. doi:10.1109/LARS64411.2024.10786404
NLM
Ferrão IG, Oliveira A de, Marçal V, Allão D, Espes D, Dezan C, Branco KRLJC. Supervised models for detecting GPS attacks and faults in UAVs: a comparative analysis [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LARS64411.2024.10786404
Vancouver
Ferrão IG, Oliveira A de, Marçal V, Allão D, Espes D, Dezan C, Branco KRLJC. Supervised models for detecting GPS attacks and faults in UAVs: a comparative analysis [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LARS64411.2024.10786404
Trabalho de evento
Riparian zones classification using Satellite/UAV synergy and deep learning (2024)
Casagrande, Luan; Hirata Júnior, Roberto
Source: Proceedings. Conference titles: IEEE International Geoscience and Remote Sensing Symposium IGARSS 2024. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, APRENDIZAGEM PROFUNDA, SATÉLITES, SENSORIAMENTO REMOTO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CASAGRANDE, Luan e HIRATA JÚNIOR, Roberto. Riparian zones classification using Satellite/UAV synergy and deep learning. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/IGARSS53475.2024.10642449. Acesso em: 08 out. 2025.
APA
Casagrande, L., & Hirata Júnior, R. (2024). Riparian zones classification using Satellite/UAV synergy and deep learning. In Proceedings. Piscataway: IEEE. doi:10.1109/IGARSS53475.2024.10642449
NLM
Casagrande L, Hirata Júnior R. Riparian zones classification using Satellite/UAV synergy and deep learning [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/IGARSS53475.2024.10642449
Vancouver
Casagrande L, Hirata Júnior R. Riparian zones classification using Satellite/UAV synergy and deep learning [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/IGARSS53475.2024.10642449
Trabalho de evento
MedTimeSplit: continual dataset partitioning to mimic real-world settings for federated learning on Non-IID medical image data (2024)
Aguiar, Erikson Júlio de ; Traina, Agma Juci Machado ; Helal, Sumi
Source: Proceedings. Conference titles: IEEE International Conference on Big Data - Big Data. Unidade: ICMC
Subjects: BANCO DE DADOS MULTIMÍDIA, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR IMAGEM, TECNOLOGIAS DA SAÚDE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
AGUIAR, Erikson Júlio de e TRAINA, Agma Juci Machado e HELAL, Sumi. MedTimeSplit: continual dataset partitioning to mimic real-world settings for federated learning on Non-IID medical image data. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/BigData62323.2024.10826044. Acesso em: 08 out. 2025.
APA
Aguiar, E. J. de, Traina, A. J. M., & Helal, S. (2024). MedTimeSplit: continual dataset partitioning to mimic real-world settings for federated learning on Non-IID medical image data. In Proceedings. Piscataway: IEEE. doi:10.1109/BigData62323.2024.10826044
NLM
Aguiar EJ de, Traina AJM, Helal S. MedTimeSplit: continual dataset partitioning to mimic real-world settings for federated learning on Non-IID medical image data [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/BigData62323.2024.10826044
Vancouver
Aguiar EJ de, Traina AJM, Helal S. MedTimeSplit: continual dataset partitioning to mimic real-world settings for federated learning on Non-IID medical image data [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/BigData62323.2024.10826044
Trabalho de evento
Deep forests with tree-embeddings and label imputation for weak-label learning (2024)
Ilídio, Pedro ; Cerri, Ricardo ; Vens, Celine ; Nakano, Felipe Kenji
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: ICMC, IFSC
Subjects: APRENDIZADO COMPUTACIONAL, FÍSICA COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ILÍDIO, Pedro et al. Deep forests with tree-embeddings and label imputation for weak-label learning. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/IJCNN60899.2024.10650456. Acesso em: 08 out. 2025.
APA
Ilídio, P., Cerri, R., Vens, C., & Nakano, F. K. (2024). Deep forests with tree-embeddings and label imputation for weak-label learning. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN60899.2024.10650456
NLM
Ilídio P, Cerri R, Vens C, Nakano FK. Deep forests with tree-embeddings and label imputation for weak-label learning [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/IJCNN60899.2024.10650456
Vancouver
Ilídio P, Cerri R, Vens C, Nakano FK. Deep forests with tree-embeddings and label imputation for weak-label learning [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/IJCNN60899.2024.10650456
Trabalho de evento
Smart self-diagnosis method for GPS attacks and safety faults in UAVs (2024)
Ferrão, Isadora Garcia ; Oliveira, André Luiz de ; Espes, David ; Dezan, Catherine ; Branco, Kalinka Regina Lucas Jaquie Castelo
Source: Proceedings. Conference titles: International Conference on Unmanned Aircraft Systems - ICUAS. Unidade: ICMC
Subjects: AERONAVES NÃO TRIPULADAS, ESPAÇO URBANO, APRENDIZADO COMPUTACIONAL, SEGURANÇA VEICULAR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FERRÃO, Isadora Garcia et al. Smart self-diagnosis method for GPS attacks and safety faults in UAVs. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/ICUAS60882.2024.10556910. Acesso em: 08 out. 2025.
APA
Ferrão, I. G., Oliveira, A. L. de, Espes, D., Dezan, C., & Branco, K. R. L. J. C. (2024). Smart self-diagnosis method for GPS attacks and safety faults in UAVs. In Proceedings. Piscataway: IEEE. doi:10.1109/ICUAS60882.2024.10556910
NLM
Ferrão IG, Oliveira AL de, Espes D, Dezan C, Branco KRLJC. Smart self-diagnosis method for GPS attacks and safety faults in UAVs [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/ICUAS60882.2024.10556910
Vancouver
Ferrão IG, Oliveira AL de, Espes D, Dezan C, Branco KRLJC. Smart self-diagnosis method for GPS attacks and safety faults in UAVs [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/ICUAS60882.2024.10556910
Trabalho de evento
Brazilian free-energy market mid- and long-term forecasting using multi-source ensemble solution (2024)
Baldo Júnior, Sérgio ; Mastelini, Saulo Martiello ; Paula, Marcos Basile Saviano de; Santos, Moises Rocha dos ; Guarnier, Ewerton ; Silva Filho, Donato da ; Santos, Maria Eugênia C. M; Fernandes, Thaina R; Rosa, Victor C. V
Source: Proceedings. Conference titles: International Conference on Machine Learning and Applications - ICMLA. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), ENERGIA ELÉTRICA, POLÍTICA DE PREÇO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BALDO JÚNIOR, Sérgio et al. Brazilian free-energy market mid- and long-term forecasting using multi-source ensemble solution. 2024, Anais.. Los Alamitos: IEEE, 2024. Disponível em: https://doi.org/10.1109/ICMLA61862.2024.00266. Acesso em: 08 out. 2025.
APA
Baldo Júnior, S., Mastelini, S. M., Paula, M. B. S. de, Santos, M. R. dos, Guarnier, E., Silva Filho, D. da, et al. (2024). Brazilian free-energy market mid- and long-term forecasting using multi-source ensemble solution. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICMLA61862.2024.00266
NLM
Baldo Júnior S, Mastelini SM, Paula MBS de, Santos MR dos, Guarnier E, Silva Filho D da, Santos MECM, Fernandes TR, Rosa VCV. Brazilian free-energy market mid- and long-term forecasting using multi-source ensemble solution [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/ICMLA61862.2024.00266
Vancouver
Baldo Júnior S, Mastelini SM, Paula MBS de, Santos MR dos, Guarnier E, Silva Filho D da, Santos MECM, Fernandes TR, Rosa VCV. Brazilian free-energy market mid- and long-term forecasting using multi-source ensemble solution [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/ICMLA61862.2024.00266

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