On the Performance of Deep Learning Models for Time Series Classification in Streaming. - Pedro Lara-Benítez; Manuel Carranza-García; Francisco Martínez-Álvarez; José C. Riquelme (SOCO, 2020)

Asynchronous dual-pipeline deep learning framework for online data stream classification. - Pedro Lara-Benítez; Manuel Carranza-García; Jorge García-Gutiérrez; José C. Riquelme (Integr. Comput. Aided Eng., 2020)

Evaluation of the Transformer Architecture for Univariate Time Series Forecasting. - Pedro Lara-Benítez; Luis Gallego-Ledesma; Manuel Carranza-García; José María Luna-Romera (CAEPIA, 2021)

Feature Selection on Spatio-Temporal Data for Solar Irradiance Forecasting. - Manuel Carranza-García; Pedro Lara-Benítez; José María Luna-Romera; José C. Riquelme (SOCO, 2021)

An Experimental Review on Deep Learning Architectures for Time Series Forecasting. - Pedro Lara-Benítez; Manuel Carranza-García; José C. Riquelme (Int. J. Neural Syst., 2021)

Enhancing object detection for autonomous driving by optimizing anchor generation and addressing class imbalance. - Manuel Carranza-García; Pedro Lara-Benítez; Jorge García-Gutiérrez; José C. Riquelme (Neurocomputing, 2021)

On the Performance of One-Stage and Two-Stage Object Detectors in Autonomous Vehicles Using Camera Data. - Manuel Carranza-García; Jesús Torres-Mateo; Pedro Lara-Benítez; Jorge García-Gutiérrez (Remote. Sens., 2021)

Short-term solar irradiance forecasting in streaming with deep learning. - Pedro Lara-Benítez; Manuel Carranza-García; José María Luna-Romera; José C. Riquelme (Neurocomputing, 2023)

Data streams classification using deep learning under different speeds and drifts. - Pedro Lara-Benítez; Manuel Carranza-García; David Gutiérrez-Avilés; José C. Riquelme (Log. J. IGPL, 2023)