Viedma, D. T., Rivera Rivas, A. J., Charte Ojeda, F., & del Jesus Díaz, M. J. (2018). Una primera aproximación a la predicción de variables turísticas con Deep Learning. 939-943. Granada (Spain). (Original work published)
Antonio Jesús Rivera Rivas
First name
Antonio Jesús
Last name
Rivera Rivas
2018
Pulgar Rubio, F. J., Charte Ojeda, F., Rivera Rivas, A. J., & del Jesus Díaz, M. J. (2018). A First Approach to Face Dimensionality Reduction Through Denoising Autoencoders. 439-447. Madrid (Spain). https://doi.org/10.1007/978-3-030-03493-1_46 (Original work published)
Pulgar Rubio, F. J., Charte Ojeda, F., Rivera Rivas, A. J., & del Jesus Díaz, M. J. (2018). AEkNN: An AutoEncoder kNN-Based Classifier With Built-in Dimensionality Reduction. International Journal of Computational Intelligence Systems, 12, 436-452. https://doi.org/10.2991/ijcis.2019.0025 (Original work published 2018)
Trujillo, D., Rivera Rivas, A. J., Charte Ojeda, F., & del Jesus Díaz, M. J. (2018). An Approximation to Deep Learning Touristic-Related Time Series Forecasting. 448-456. Madrid (Spain). https://doi.org/10.1007/978-3-030-03493-1_47 (Original work published)
Pulgar Rubio, F. J., Rivera Rivas, A. J., Charte Ojeda, F., & del Jesus Díaz, M. J. (2018). Análisis del impacto de datos desbalanceados en el rendimiento predictivo de redes neuronales convolucionales. 1213-1218. Granada (Spain). (Original work published)
2017
Charte Ojeda, F., Romero, I., Rivera Rivas, A. J., & Castro, E. (2017). Modeling the Transformation of Olive Tree Biomass into Bioethanol with Reg-CO2RBFN. 733-744. Cádiz (Spain). https://doi.org/10.1007/978-3-319-59153-7_63 (Original work published)
Pulgar Rubio, F. J., Rivera Rivas, A. J., Charte Ojeda, F., & del Jesus Díaz, M. J. (2017). On the Impact of Imbalanced Data in Convolutional Neural Networks Performance. 220-232. La Rioja (Spain). https://doi.org/10.1007/978-3-319-59650-1_19 (Original work published)
Charte Ojeda, F., Espinilla, M., Rivera Rivas, A. J., & Pulgar Rubio, F. J. (2017). Uso de dispositivos FPGA como apoyo a la enseñanza de asignaturas de arquitectura de computadores. Enseñanza y aprendizaje de ingeniería de computadores. Revista de experiencias docentes en ingeniería de computadores, 7, 37-52.
Martínez, F., Frías Bustamante, M. del P., Pérez Godoy, M. D., & Rivera Rivas, A. J. (2017). A methodology for applying k-nearest neighbor to time series forecasting. Artificial Intelligence Review. https://doi.org/10.1007/s10462-017-9593-z (Original work published 2026)
Martínez, F., Frías, M., Charte Ojeda, F., & Rivera Rivas, A. J. (2017). A specialized lazy learner for time series forecasting. 1397-1403. Costa Ballena, Rota, Cáadiz (Spain). (Original work published)