ReP USP - Resultado da busca

Artigo de periodico
Mandible and skull segmentation in cone beam computed tomography using super-voxels and graph clustering (2019)
Linares, Oscar Cuadros; Bianchi, Jonas ; Raveli, Dirceu ; Batista Neto, João do Espírito Santo ; Hamann, Bernd
Fonte: Visual Computer. Unidade: ICMC
Assuntos: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, DIAGNÓSTICO POR COMPUTADOR, ANOMALIA CRANIOFACIAL, TOMOGRAFIA
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ABNT
LINARES, Oscar Cuadros et al. Mandible and skull segmentation in cone beam computed tomography using super-voxels and graph clustering. Visual Computer, v. 35, n. 10, p. 1461-1474, 2019Tradução . . Disponível em: https://doi.org/10.1007/s00371-018-1511-0. Acesso em: 12 out. 2024.
APA
Linares, O. C., Bianchi, J., Raveli, D., Batista Neto, J. do E. S., & Hamann, B. (2019). Mandible and skull segmentation in cone beam computed tomography using super-voxels and graph clustering. Visual Computer, 35( 10), 1461-1474. doi:10.1007/s00371-018-1511-0
NLM
Linares OC, Bianchi J, Raveli D, Batista Neto J do ES, Hamann B. Mandible and skull segmentation in cone beam computed tomography using super-voxels and graph clustering [Internet]. Visual Computer. 2019 ; 35( 10): 1461-1474.[citado 2024 out. 12 ] Available from: https://doi.org/10.1007/s00371-018-1511-0
Vancouver
Linares OC, Bianchi J, Raveli D, Batista Neto J do ES, Hamann B. Mandible and skull segmentation in cone beam computed tomography using super-voxels and graph clustering [Internet]. Visual Computer. 2019 ; 35( 10): 1461-1474.[citado 2024 out. 12 ] Available from: https://doi.org/10.1007/s00371-018-1511-0
Trabalho de evento
Understanding pedestrian-vehicle interactions with vehicle mounted vision: an LSTM model and empirical analysis (2019)
Ridel, Daniela Alves; Deo, Nachiket; Wolf, Denis Fernando ; Trivedi, Mohan
Fonte: Proceedings. Nome do evento: IEEE Intelligent Vehicles Symposium - IV. Unidade: ICMC
Assuntos: CIRCULAÇÃO DE PEDESTRES, VEÍCULOS AUTÔNOMOS, TRÁFEGO RODOVIÁRIO, ANÁLISE DE TRAJETÓRIAS
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ABNT
RIDEL, Daniela Alves et al. Understanding pedestrian-vehicle interactions with vehicle mounted vision: an LSTM model and empirical analysis. 2019, Anais.. Piscataway: IEEE, 2019. Disponível em: https://doi.org/10.1109/IVS.2019.8813798. Acesso em: 12 out. 2024.
APA
Ridel, D. A., Deo, N., Wolf, D. F., & Trivedi, M. (2019). Understanding pedestrian-vehicle interactions with vehicle mounted vision: an LSTM model and empirical analysis. In Proceedings. Piscataway: IEEE. doi:10.1109/IVS.2019.8813798
NLM
Ridel DA, Deo N, Wolf DF, Trivedi M. Understanding pedestrian-vehicle interactions with vehicle mounted vision: an LSTM model and empirical analysis [Internet]. Proceedings. 2019 ;[citado 2024 out. 12 ] Available from: https://doi.org/10.1109/IVS.2019.8813798
Vancouver
Ridel DA, Deo N, Wolf DF, Trivedi M. Understanding pedestrian-vehicle interactions with vehicle mounted vision: an LSTM model and empirical analysis [Internet]. Proceedings. 2019 ;[citado 2024 out. 12 ] Available from: https://doi.org/10.1109/IVS.2019.8813798
Artigo de periodico
Fast similarity matrix profile for music analysis and exploration (2019)
Silva, Diego Furtado ; Yeh, Chin-Chin M; Zhu, Yan; Batista, Gustavo Enrique de Almeida Prado Alves; Keogh, Eamonn
Fonte: IEEE Transactions on Multimedia. Unidade: ICMC
Assuntos: RECUPERAÇÃO DA INFORMAÇÃO, MINERAÇÃO DE DADOS, MÚSICA
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ABNT
SILVA, Diego Furtado et al. Fast similarity matrix profile for music analysis and exploration. IEEE Transactions on Multimedia, v. 21, n. Ja 2019, p. 29-38, 2019Tradução . . Disponível em: https://doi.org/10.1109/TMM.2018.2849563. Acesso em: 12 out. 2024.
APA
Silva, D. F., Yeh, C. -C. M., Zhu, Y., Batista, G. E. de A. P. A., & Keogh, E. (2019). Fast similarity matrix profile for music analysis and exploration. IEEE Transactions on Multimedia, 21( Ja 2019), 29-38. doi:10.1109/TMM.2018.2849563
NLM
Silva DF, Yeh C-CM, Zhu Y, Batista GE de APA, Keogh E. Fast similarity matrix profile for music analysis and exploration [Internet]. IEEE Transactions on Multimedia. 2019 ; 21( Ja 2019): 29-38.[citado 2024 out. 12 ] Available from: https://doi.org/10.1109/TMM.2018.2849563
Vancouver
Silva DF, Yeh C-CM, Zhu Y, Batista GE de APA, Keogh E. Fast similarity matrix profile for music analysis and exploration [Internet]. IEEE Transactions on Multimedia. 2019 ; 21( Ja 2019): 29-38.[citado 2024 out. 12 ] Available from: https://doi.org/10.1109/TMM.2018.2849563
Trabalho de evento
Large-scale similarity-based time series mining (2018)
Silva, Diego Furtado ; Batista, Gustavo Enrique de Almeida Prado Alves (Orientador) ; Keogh, Eamonn (coorient)
Fonte: Anais. Nome do evento: Congresso da Sociedade Brasileira de Computação - CSBC. Unidade: ICMC
Assuntos: MINERAÇÃO DE DADOS, ANÁLISE DE SÉRIES TEMPORAIS, ALGORITMOS ÚTEIS E ESPECÍFICOS
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ABNT
SILVA, Diego Furtado. Large-scale similarity-based time series mining. 2018, Anais.. Porto Alegre: SBC, 2018. Disponível em: https://sol.sbc.org.br/index.php/ctd/article/view/3656/3608. Acesso em: 12 out. 2024.
APA
Silva, D. F. (2018). Large-scale similarity-based time series mining. In Anais. Porto Alegre: SBC. Recuperado de https://sol.sbc.org.br/index.php/ctd/article/view/3656/3608
NLM
Silva DF. Large-scale similarity-based time series mining [Internet]. Anais. 2018 ;[citado 2024 out. 12 ] Available from: https://sol.sbc.org.br/index.php/ctd/article/view/3656/3608
Vancouver
Silva DF. Large-scale similarity-based time series mining [Internet]. Anais. 2018 ;[citado 2024 out. 12 ] Available from: https://sol.sbc.org.br/index.php/ctd/article/view/3656/3608
Trabalho de evento
Prefix and suffix invariant dynamic time warping (2016)
Silva, Diego Furtado ; Batista, Gustavo Enrique de Almeida Prado Alves; Keogh, Eamonn
Fonte: Proceedings. Nome do evento: IEEE International Conference on Data Mining - ICDM. Unidade: ICMC
Assuntos: MINERAÇÃO DE DADOS, ALGORITMOS, ANÁLISE DE SÉRIES TEMPORAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVA, Diego Furtado e BATISTA, Gustavo Enrique de Almeida Prado Alves e KEOGH, Eamonn. Prefix and suffix invariant dynamic time warping. 2016, Anais.. Los Alamitos: IEEE, 2016. Disponível em: https://doi.org/10.1109/ICDM.2016.0161. Acesso em: 12 out. 2024.
APA
Silva, D. F., Batista, G. E. de A. P. A., & Keogh, E. (2016). Prefix and suffix invariant dynamic time warping. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICDM.2016.0161
NLM
Silva DF, Batista GE de APA, Keogh E. Prefix and suffix invariant dynamic time warping [Internet]. Proceedings. 2016 ;[citado 2024 out. 12 ] Available from: https://doi.org/10.1109/ICDM.2016.0161
Vancouver
Silva DF, Batista GE de APA, Keogh E. Prefix and suffix invariant dynamic time warping [Internet]. Proceedings. 2016 ;[citado 2024 out. 12 ] Available from: https://doi.org/10.1109/ICDM.2016.0161
Trabalho de evento
On the effect of endpoints on dynamic time warping (2016)
Silva, Diego Furtado ; Batista, Gustavo Enrique de Almeida Prado Alves; Keogh, Eamonn
Fonte: Proceedings. Nome do evento: SIGKDD Workshop on Mining and Learning from Time Series - SIGKDD MiLeTS. Unidade: ICMC
Assuntos: INTELIGÊNCIA ARTIFICIAL, MINERAÇÃO DE DADOS, ANÁLISE DE SÉRIES TEMPORAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVA, Diego Furtado e BATISTA, Gustavo Enrique de Almeida Prado Alves e KEOGH, Eamonn. On the effect of endpoints on dynamic time warping. 2016, Anais.. New York: ACM, 2016. Disponível em: https://doi.org/10.1145/12345.67890. Acesso em: 12 out. 2024.
APA
Silva, D. F., Batista, G. E. de A. P. A., & Keogh, E. (2016). On the effect of endpoints on dynamic time warping. In Proceedings. New York: ACM. doi:10.1145/12345.67890
NLM
Silva DF, Batista GE de APA, Keogh E. On the effect of endpoints on dynamic time warping [Internet]. Proceedings. 2016 ;[citado 2024 out. 12 ] Available from: https://doi.org/10.1145/12345.67890
Vancouver
Silva DF, Batista GE de APA, Keogh E. On the effect of endpoints on dynamic time warping [Internet]. Proceedings. 2016 ;[citado 2024 out. 12 ] Available from: https://doi.org/10.1145/12345.67890
Parte de monografia/livro
Automatic insect classification using Bayesian classifier and audio processing features (2015)
Silva, Diego Furtado ; Chen, Y; Why, A; Keogh, E. J; Batista, Gustavo Enrique de Almeida Prado Alves
Fonte: The plant protection data toolbox. Unidade: ICMC
Assuntos: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, CONTROLE DE INSETOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVA, Diego Furtado et al. Automatic insect classification using Bayesian classifier and audio processing features. The plant protection data toolbox. Tradução . Caxton: New Zealand Plant Protection Society, 2015. . . Acesso em: 12 out. 2024.
APA
Silva, D. F., Chen, Y., Why, A., Keogh, E. J., & Batista, G. E. de A. P. A. (2015). Automatic insect classification using Bayesian classifier and audio processing features. In The plant protection data toolbox. Caxton: New Zealand Plant Protection Society.
NLM
Silva DF, Chen Y, Why A, Keogh EJ, Batista GE de APA. Automatic insect classification using Bayesian classifier and audio processing features. In: The plant protection data toolbox. Caxton: New Zealand Plant Protection Society; 2015. [citado 2024 out. 12 ]
Vancouver
Silva DF, Chen Y, Why A, Keogh EJ, Batista GE de APA. Automatic insect classification using Bayesian classifier and audio processing features. In: The plant protection data toolbox. Caxton: New Zealand Plant Protection Society; 2015. [citado 2024 out. 12 ]
Artigo de periodico
CID: an efficient complexity-invariant distance for time series (2014)
Batista, Gustavo Enrique de Almeida Prado Alves; Keogh, Eamonn J; Tataw, Oben Moses; Souza, Vinícius M. A. de
Fonte: Data Mining and Knowledge Discovery. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BATISTA, Gustavo Enrique de Almeida Prado Alves et al. CID: an efficient complexity-invariant distance for time series. Data Mining and Knowledge Discovery, v. 28, n. 3, p. 634-669, 2014Tradução . . Disponível em: https://doi.org/10.1007/s10618-013-0312-3. Acesso em: 12 out. 2024.
APA
Batista, G. E. de A. P. A., Keogh, E. J., Tataw, O. M., & Souza, V. M. A. de. (2014). CID: an efficient complexity-invariant distance for time series. Data Mining and Knowledge Discovery, 28( 3), 634-669. doi:10.1007/s10618-013-0312-3
NLM
Batista GE de APA, Keogh EJ, Tataw OM, Souza VMA de. CID: an efficient complexity-invariant distance for time series [Internet]. Data Mining and Knowledge Discovery. 2014 ; 28( 3): 634-669.[citado 2024 out. 12 ] Available from: https://doi.org/10.1007/s10618-013-0312-3
Vancouver
Batista GE de APA, Keogh EJ, Tataw OM, Souza VMA de. CID: an efficient complexity-invariant distance for time series [Internet]. Data Mining and Knowledge Discovery. 2014 ; 28( 3): 634-669.[citado 2024 out. 12 ] Available from: https://doi.org/10.1007/s10618-013-0312-3
Artigo de periodico
Addressing big data time series: mining trillions of time series subsequences under dynamic time warping (2013)
Rakthanmanon, Thanawin; Campana, Bilson; Mueen, Abdullah; Batista, Gustavo Enrique de Almeida Prado Alves; Westover, Brandon; Zhu, Qiang; Zakaria, Jesin; Keogh, Eamonn
Fonte: ACM Transactions on Knowledge Discovery from Data - TKDD. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RAKTHANMANON, Thanawin et al. Addressing big data time series: mining trillions of time series subsequences under dynamic time warping. ACM Transactions on Knowledge Discovery from Data - TKDD, v. 7, n. 3, p. 10:1-10:31, 2013Tradução . . Disponível em: https://doi.org/10.1145/2500489. Acesso em: 12 out. 2024.
APA
Rakthanmanon, T., Campana, B., Mueen, A., Batista, G. E. de A. P. A., Westover, B., Zhu, Q., et al. (2013). Addressing big data time series: mining trillions of time series subsequences under dynamic time warping. ACM Transactions on Knowledge Discovery from Data - TKDD, 7( 3), 10:1-10:31. doi:10.1145/2500489
NLM
Rakthanmanon T, Campana B, Mueen A, Batista GE de APA, Westover B, Zhu Q, Zakaria J, Keogh E. Addressing big data time series: mining trillions of time series subsequences under dynamic time warping [Internet]. ACM Transactions on Knowledge Discovery from Data - TKDD. 2013 ; 7( 3): 10:1-10:31.[citado 2024 out. 12 ] Available from: https://doi.org/10.1145/2500489
Vancouver
Rakthanmanon T, Campana B, Mueen A, Batista GE de APA, Westover B, Zhu Q, Zakaria J, Keogh E. Addressing big data time series: mining trillions of time series subsequences under dynamic time warping [Internet]. ACM Transactions on Knowledge Discovery from Data - TKDD. 2013 ; 7( 3): 10:1-10:31.[citado 2024 out. 12 ] Available from: https://doi.org/10.1145/2500489
Trabalho de evento
Applying machine learning and audio analysis techniques to insect recognition in intelligent traps (2013)
Silva, Diego Furtado ; Souza, Vinícius M. A. de; Batista, Gustavo Enrique de Almeida Prado Alves; Keogh, Eamonn; Ellis, Daniel P. W
Fonte: Proceedings. Nome do evento: International Conference on Machine Learning and Applications - ICMLA. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVA, Diego Furtado et al. Applying machine learning and audio analysis techniques to insect recognition in intelligent traps. 2013, Anais.. Los Alamitos: CPS/IEEE, 2013. Disponível em: https://doi.org/10.1109/ICMLA.2013.24. Acesso em: 12 out. 2024.
APA
Silva, D. F., Souza, V. M. A. de, Batista, G. E. de A. P. A., Keogh, E., & Ellis, D. P. W. (2013). Applying machine learning and audio analysis techniques to insect recognition in intelligent traps. In Proceedings. Los Alamitos: CPS/IEEE. doi:10.1109/ICMLA.2013.24
NLM
Silva DF, Souza VMA de, Batista GE de APA, Keogh E, Ellis DPW. Applying machine learning and audio analysis techniques to insect recognition in intelligent traps [Internet]. Proceedings. 2013 ;[citado 2024 out. 12 ] Available from: https://doi.org/10.1109/ICMLA.2013.24
Vancouver
Silva DF, Souza VMA de, Batista GE de APA, Keogh E, Ellis DPW. Applying machine learning and audio analysis techniques to insect recognition in intelligent traps [Internet]. Proceedings. 2013 ;[citado 2024 out. 12 ] Available from: https://doi.org/10.1109/ICMLA.2013.24
Trabalho de evento
DTW-D: time series semi-supervised learning from a single example (2013)
Chen, Yanping; Hu, Bing; Keogh, Eamonn; Batista, Gustavo Enrique de Almeida Prado Alves
Fonte: Proceedings. Nome do evento: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
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ABNT
CHEN, Yanping et al. DTW-D: time series semi-supervised learning from a single example. 2013, Anais.. New York: ACM, 2013. Disponível em: https://doi.org/10.1145/2487575.2487633. Acesso em: 12 out. 2024.
APA
Chen, Y., Hu, B., Keogh, E., & Batista, G. E. de A. P. A. (2013). DTW-D: time series semi-supervised learning from a single example. In Proceedings. New York: ACM. doi:10.1145/2487575.2487633
NLM
Chen Y, Hu B, Keogh E, Batista GE de APA. DTW-D: time series semi-supervised learning from a single example [Internet]. Proceedings. 2013 ;[citado 2024 out. 12 ] Available from: https://doi.org/10.1145/2487575.2487633
Vancouver
Chen Y, Hu B, Keogh E, Batista GE de APA. DTW-D: time series semi-supervised learning from a single example [Internet]. Proceedings. 2013 ;[citado 2024 out. 12 ] Available from: https://doi.org/10.1145/2487575.2487633
Trabalho de evento
Data mining a trillion time series subsequences under dynamic time warping (2013)
Rakthanmanon, Thanawin; Campana, Bilson; Mueen, Abdullah; Batista, Gustavo Enrique de Almeida Prado Alves; Westover, Brandon; Qiang, Zhu; Zakaria, Jesin; Keogh, Eamonn
Fonte: Proceedings. Nome do evento: International Joint Conference on Artificial Intelligence - IJCAI. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
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ABNT
RAKTHANMANON, Thanawin et al. Data mining a trillion time series subsequences under dynamic time warping. 2013, Anais.. Menlo Park: AAAI Press, 2013. Disponível em: http://ijcai.org/papers13/Papers/IJCAI13-454.pdf. Acesso em: 12 out. 2024.
APA
Rakthanmanon, T., Campana, B., Mueen, A., Batista, G. E. de A. P. A., Westover, B., Qiang, Z., et al. (2013). Data mining a trillion time series subsequences under dynamic time warping. In Proceedings. Menlo Park: AAAI Press. Recuperado de http://ijcai.org/papers13/Papers/IJCAI13-454.pdf
NLM
Rakthanmanon T, Campana B, Mueen A, Batista GE de APA, Westover B, Qiang Z, Zakaria J, Keogh E. Data mining a trillion time series subsequences under dynamic time warping [Internet]. Proceedings. 2013 ;[citado 2024 out. 12 ] Available from: http://ijcai.org/papers13/Papers/IJCAI13-454.pdf
Vancouver
Rakthanmanon T, Campana B, Mueen A, Batista GE de APA, Westover B, Qiang Z, Zakaria J, Keogh E. Data mining a trillion time series subsequences under dynamic time warping [Internet]. Proceedings. 2013 ;[citado 2024 out. 12 ] Available from: http://ijcai.org/papers13/Papers/IJCAI13-454.pdf
Trabalho de evento
A novel approximation to dynamic time warping allows anytime clustering of massive time series datasets (2012)
Qiang, Zhu; Batista, Gustavo Enrique de Almeida Prado Alves; Rakthanmanon, Thanawin; Keogh, Eamonn
Fonte: Proceedings. Nome do evento: SIAM International Conference on Data Mining. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
QIANG, Zhu et al. A novel approximation to dynamic time warping allows anytime clustering of massive time series datasets. 2012, Anais.. Philadelphia: SIAM, 2012. Disponível em: http://siam.omnibooksonline.com/2012datamining/. Acesso em: 12 out. 2024.
APA
Qiang, Z., Batista, G. E. de A. P. A., Rakthanmanon, T., & Keogh, E. (2012). A novel approximation to dynamic time warping allows anytime clustering of massive time series datasets. In Proceedings. Philadelphia: SIAM. Recuperado de http://siam.omnibooksonline.com/2012datamining/
NLM
Qiang Z, Batista GE de APA, Rakthanmanon T, Keogh E. A novel approximation to dynamic time warping allows anytime clustering of massive time series datasets [Internet]. Proceedings. 2012 ;[citado 2024 out. 12 ] Available from: http://siam.omnibooksonline.com/2012datamining/
Vancouver
Qiang Z, Batista GE de APA, Rakthanmanon T, Keogh E. A novel approximation to dynamic time warping allows anytime clustering of massive time series datasets [Internet]. Proceedings. 2012 ;[citado 2024 out. 12 ] Available from: http://siam.omnibooksonline.com/2012datamining/
Trabalho de evento
Searching and mining trillions of time series subsequences under dynamic time warping (2012)
Rakthanmanon, Thanawin; Campana, Bilson; Mueen, Abdullah; Batista, Gustavo Enrique de Almeida Prado Alves; Westover, Brandon; Qiang, Zhu; Zakaria, Jesin; Keogh, Eamonn
Fonte: Proceedings. Nome do evento: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RAKTHANMANON, Thanawin et al. Searching and mining trillions of time series subsequences under dynamic time warping. 2012, Anais.. New York: ACM, 2012. Disponível em: https://doi.org/10.1145/2339530.2339576. Acesso em: 12 out. 2024.
APA
Rakthanmanon, T., Campana, B., Mueen, A., Batista, G. E. de A. P. A., Westover, B., Qiang, Z., et al. (2012). Searching and mining trillions of time series subsequences under dynamic time warping. In Proceedings. New York: ACM. doi:10.1145/2339530.2339576
NLM
Rakthanmanon T, Campana B, Mueen A, Batista GE de APA, Westover B, Qiang Z, Zakaria J, Keogh E. Searching and mining trillions of time series subsequences under dynamic time warping [Internet]. Proceedings. 2012 ;[citado 2024 out. 12 ] Available from: https://doi.org/10.1145/2339530.2339576
Vancouver
Rakthanmanon T, Campana B, Mueen A, Batista GE de APA, Westover B, Qiang Z, Zakaria J, Keogh E. Searching and mining trillions of time series subsequences under dynamic time warping [Internet]. Proceedings. 2012 ;[citado 2024 out. 12 ] Available from: https://doi.org/10.1145/2339530.2339576
Trabalho de evento
Towards automatic classification on flying insects using inexpensive sensors (2011)
Batista, Gustavo Enrique de Almeida Prado Alves; Hao, Yuan; Keogh, Eamonn; Mafra-Neto, Agenor
Fonte: Proceedings. Nome do evento: International Conference on Machine Learning and Applications - ICMLA. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BATISTA, Gustavo Enrique de Almeida Prado Alves et al. Towards automatic classification on flying insects using inexpensive sensors. 2011, Anais.. Los Alamitos: IEEE Computer Society, 2011. Disponível em: https://doi.org/10.1109/ICMLA.2011.145. Acesso em: 12 out. 2024.
APA
Batista, G. E. de A. P. A., Hao, Y., Keogh, E., & Mafra-Neto, A. (2011). Towards automatic classification on flying insects using inexpensive sensors. In Proceedings. Los Alamitos: IEEE Computer Society. doi:10.1109/ICMLA.2011.145
NLM
Batista GE de APA, Hao Y, Keogh E, Mafra-Neto A. Towards automatic classification on flying insects using inexpensive sensors [Internet]. Proceedings. 2011 ;[citado 2024 out. 12 ] Available from: https://doi.org/10.1109/ICMLA.2011.145
Vancouver
Batista GE de APA, Hao Y, Keogh E, Mafra-Neto A. Towards automatic classification on flying insects using inexpensive sensors [Internet]. Proceedings. 2011 ;[citado 2024 out. 12 ] Available from: https://doi.org/10.1109/ICMLA.2011.145

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