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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 32 publicaciones

CARHUANCHO, C. A.; VILLANUEVA, E. R.; YARLEQUÉ, C. P.; PRINCIPE, R. E.; CASTROMONTE, M. C.(2025). Generating high-resolution climate data in the Andes using artificial intelligence: A lightweight alternative to the WRF model. Artificial Intelligence in Geosciences. Volumen: 6. (pp. 100143). Recuperado de: https://www.sciencedirect.com/science/article/pii/S2666544125000395
MAMANI, Y. y VILLANUEVA, E. R.(2024). A Review on Text Sentiment Analysis With Machine Learning and Deep Learning Techniques. IEEE Access. Volumen: 12. (pp. 193115 - 193130). Recuperado de: https://ieeexplore.ieee.org/abstract/document/10786014
APAZA, J. P. y VILLANUEVA, E. R.(2024). Detection of Geometric Elements in Axonometric Projection Images Using Computer Vision Techniques. En 12th IEEE Andescon, ANDESCON 2024. (pp. 1 - 6). Institute of Electrical and Electronics Engineers Inc.. Recuperado de: https://ieeexplore.ieee.org/abstract/document/10755621
ESPEZUA, S.; Caballero, R. F.; VILLANUEVA, E. R.(2024). Enhanced Calibration Techniques for Low-Cost Particulate Matter Monitors. En 2024 IEEE XXXI International Conference on Electronics, Electrical Engineering and Computing (INTERCON). (pp. 1 - 8). Institute of Electrical and Electronics Engineers Inc.. Recuperado de: https://ieeexplore.ieee.org/abstract/document/10833487
RODRIGUEZ, G. P. G.; VILLANUEVA, E. R.; BALDEON, J. P.(2024). Enhancing Pokémon VGC Player Performance: Intelligent Agents Through Deep Reinforcement Learning and Neuroevolution. En 6th International Conference, HCI-Games 2024, Held as Part of the 26th HCI International Conference, HCII 2024. (pp. 275 - 294). CHAM. Springer. Recuperado de: https://link.springer.com/chapter/10.1007/978-3-031-60692-2_19
CARHUAS, M. C.; ESPEZUA, S.; VILLANUEVA, E. R.(2024). On Multi-Horizon Forecasting of Copper Price Returns Using Deep Learning Techniques. En 12th IEEE Andescon, ANDESCON 2024. (pp. 1 - 7). Institute of Electrical and Electronics Engineers Inc.. Recuperado de: https://ieeexplore.ieee.org/abstract/document/10755892
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