| Princípios de Análise e Projeto de Sistemas com UML, 3ª edição E Bezerra Elsevier Brasil 3, http://eic.cefet-rj.br/papsuml3ed/, 2015 | 618* | 2015 |
| Data mining R Goldschmidt, E Passos, E Bezerra Elsevier Brasil, 2015 | 208 | 2015 |
| Stconvs2s: Spatiotemporal convolutional sequence to sequence network for weather forecasting R Castro, YM Souto, E Ogasawara, F Porto, E Bezerra Neurocomputing 426, 285-298, 2021 | 90 | 2021 |
| Introdução à aprendizagem profunda E Bezerra Artigo–31º Simpósio Brasileiro de Banco de Dados–SBBD2016–Salvador, 2016 | 32 | 2016 |
| Evaluating temporal aggregation for predicting the sea surface temperature of the Atlantic Ocean R Salles, P Mattos, AMD Iorgulescu, E Bezerra, L Lima, E Ogasawara Ecological Informatics 36, 94-105, 2016 | 29 | 2016 |
| GOA++: Tecnologia, implementação e extensões aos serviços de gerência de objetos R Mauro, G Zimbrão, TS Brügger, FO Tavares, M Duran, AAB Lima, ... XII Simp. Bras. de Banco de Dados, 272-286, 1997 | 27* | 1997 |
| A Population-Based Hybrid Approach for Hyperparameter Optimization of Neural Networks L Japa, M Serqueira, I Mendonça, M Aritsugi, E Bezerra, PH González arXiv preprint arXiv:2011.11062, 2020 | 21 | 2020 |
| A spatiotemporal ensemble approach to rainfall forecasting YM Souto, F Porto, AM Moura, E Bezerra 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 21 | 2018 |
| Discovering top-k non-redundant clusterings in attributed graphs GP Guedes, E Ogasawara, E Bezerra, G Xexeo Neurocomputing 210, 45-54, 2016 | 17 | 2016 |
| A framework for benchmarking machine learning methods using linear models for univariate time series prediction R Salles, L Assis, G Guedes, E Bezerra, F Porto, E Ogasawara 2017 International Joint Conference on Neural Networks (IJCNN), 2338-2345, 2017 | 15 | 2017 |
| Persistência de Componentes num Ambiente de Reuso M Mattoso, C Werner, R Braga, R Pinheiro, L Murta, V Almeida, M Costa, ... XIV Simpósio Brasileiro de Engenharia de Software, 251-254, 2000 | 12 | 2000 |
| A deep reinforcement learning approach to asset-liability management A Fontoura, D Haddad, E Bezerra 2019 8th Brazilian Conference on Intelligent Systems (BRACIS), 216-221, 2019 | 11 | 2019 |
| An analysis of the integration between data mining applications and database systems E Bezerra, M Mattoso, G Xexeo WIT Transactions on Information and Communication Technologies 25, 2000 | 11 | 2000 |
| Exploring machine learning methods for the star/galaxy separation problem E Machado, M Serqueira, E Ogasawara, R Ogando, MAG Maia, ... 2016 International Joint Conference on Neural Networks (IJCNN), 123-130, 2016 | 10 | 2016 |
| An analysis of malaria in the Brazilian Legal Amazon using divergent association rules L Baroni, R Salles, S Salles, G Guedes, F Porto, E Bezerra, C Barcellos, ... Journal of Biomedical Informatics 108, 103512, 2020 | 9 | 2020 |
| A Bimodal Learning Approach to Assist Multi-sensory Effects Synchronization R Abreu, J dos Santos, E Bezerra | 9 | 2018 |
| Machine learning approaches to extreme weather events forecast in urban areas: Challenges and initial results F Porto, M Ferro, E Ogasawara, T Moeda, CDT de Barros, AC Silva, ... Supercomputing Frontiers and Innovations 9 (1), 49-73, 2022 | 8 | 2022 |
| A conjugated evolutionary algorithm for hyperparameter optimization L Japa, M Serqueira, I Mendonça, E Bezerra, M Aritsugi, PH González 2022 IEEE Congress on Evolutionary Computation (CEC), 1-9, 2022 | 7 | 2022 |
| TSPred: a framework for nonstationary time series prediction R Salles, E Pacitti, E Bezerra, F Porto, E Ogasawara Neurocomputing 467, 197-202, 2022 | 7 | 2022 |
| Evaluating Linear Models as a Baseline for Time Series Imputation. R Salles, E Bezerra, J de Abreu Soares, ES Ogasawara SBBD (Short Papers), 63-68, 2015 | 7 | 2015 |
Eduardo OgasawaraCEFET/RJEmail verificata su ieee.org