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EDWIN RAFAEL VILLANUEVA TALAVERA

EDWIN RAFAEL VILLANUEVA TALAVERA

EDWIN RAFAEL VILLANUEVA TALAVERA

DOUTOR EM CIÊNCIAS, Universidade de Sao Paulo-Escola de Engenharia de Sao Carlo

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Mestre em Engenharia Elétrica (Universidade de Sao Paulo-Escola de Engenharia de Sao Carlo)

DOCENTE ORDINARIO - ASOCIADO
Docente a tiempo completo (DTC)
Departamento Académico de Ingeniería - Sección Ingeniería Informática

Publicaciones

Se encontraron 26 publicaciones

VILLANUEVA, E. R.; ESPEZUA, S.; Castelar, G.; Diaz, K.; Ingaroca, E.(2023). Smart Multi-Sensor Calibration of Low-Cost Particulate Matter Monitors. SENSORS. Volumen: 7. (pp. 3776). Recuperado de: https://www.mdpi.com/1424-8220/23/7/3776
MONTALVO, L. G.; FOSCA, D.; PAREDES, D. J.; ABARCA, M. L.; SAITO, C.; VILLANUEVA, E. R.(2022). An Air Quality Monitoring and Forecasting System for Lima City With Low-Cost Sensors and Artificial Intelligence Models. Frontiers in Sustainable Cities. Volumen: 4. Recuperado de: https://www.frontiersin.org/articles/10.3389/frsc.2022.849762/full
CABRERA, J. J. y VILLANUEVA, E. R.(2022). Investigating Generative Neural-Network Models for Building Pest Insect Detectors in Sticky Trap Images for the Peruvian Horticulture. En 8th Annual International Conference on Information Management and Big Data. (pp. 356 - 369). NUEVA YORK. Springer, Cham. Recuperado de: https://link.springer.com/chapter/10.1007/978-3-031-04447-2_24
ULLOA, A. E.; ESPEZUA, S.; VILLAVICENCIO, J. A.; MIRANDA, O. E.; VILLANUEVA, E. R.(2022). Predicting Daily Trends in the Lima Stock Exchange General Index Using Economic Indicators and Financial News Sentiments. En 8th Annual International Conference on Information Management and Big Data. (pp. 34 - 39). NUEVA YORK. Springer, Cham. Recuperado de: https://link.springer.com/chapter/10.1007/978-3-031-04447-2_3
HUAMAN, M. H. S.; CABRERA, J. J.; IBAÑEZ, D. H.; JIMENEZ, A. B.; BELTRAN, C. A.; VILLANUEVA, E. R.(2022). Unpaired Faces to Cartoons: Improving XGAN. En 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). (pp. 1517 - 1526). IEEE. Recuperado de: https://ieeexplore.ieee.org/document/9857127
Colchado, L.; VILLANUEVA, E. R.; Ochoa, J.(2021). A Neural Network Architecture with an Attention-based Layer for Spatial Prediction of Fine Particulate Matter. En 8th IEEE International Conference on Data Science and Advanced Analytics (DSAA). (pp. 1 - 10). Porto. IEEE COMPUTER SOC. Recuperado de: https://ieeexplore.ieee.org/abstract/document/9564200
DEL RIO, S. A. y VILLANUEVA, E. R.(2021). A Novel Method to Estimate Parents and Children for Local Bayesian Network Learning. En Intelligent Systems and Applications Conference (IntelliSys 2021). (pp. 468 - 485). Springer, Cham. Recuperado de: https://link.springer.com/chapter/10.1007%2F978-3-030-82196-8_35
VARGAS, I. R. y VILLANUEVA, E. R.(2021). Comparative Study of Spatial Prediction Models for Estimating PM 2.5 Concentration Level in Urban Areas. En 7th Annual International Conference on Information Management and Big Data. (pp. 169 - 180). Springer, Cham. Recuperado de: https://link.springer.com/chapter/10.1007%2F978-3-030-76228-5_12