A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks. - Manuel Carranza-García; Jorge García-Gutiérrez; José C. Riquelme (Remote. Sens., 2019)

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)

Study Case of Household Electricity Consumption Patterns in London by Clustering Methodology. - José María Luna-Romera; Manuel Carranza-García; David Gutiérrez-Avilés; José Cristóbal Riquelme Santos (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)

Concept Drift Detection to Improve Time Series Forecasting of Wind Energy Generation. - Tomás Cabello-López; Manuel Cañizares-Juan; Manuel Carranza-García; Jorge García-Gutiérrez; José C. Riquelme (HAIS, 2022)

Temporal Axial Attention For Lidar-Based 3d Object Detection In Autonomous Driving. - Manuel Carranza-García; José C. Riquelme; Avideh Zakhor (ICIP, 2022)

Object detection using depth completion and camera-LiDAR fusion for autonomous driving. - Manuel Carranza-García; Francisco Javier Galán-Sales; José María Luna-Romera; José C. Riquelme (Integr. Comput. Aided Eng., 2022)

Association Rule Analysis of Student Satisfaction Surveys for Teaching Quality Evaluation. - Manuel Jesús Jiménez-Navarro; Belén Vega-Márquez; José María Luna-Romera; Manuel Carranza-García; María Martínez-Ballesteros (CISIS-ICEUTE, 2023)

An Approach to Enhance Time Series Forecasting by Fast Fourier Transform. - Francisco Javier Galán-Sales; Pablo Reina-Jiménez; Manuel Carranza-García; José María Luna-Romera (SOCO (1), 2023)

Efficient Short-Term Time Series Forecasting with Regression Trees. - Pablo Reina-Jiménez; Manuel Carranza-García; José María Luna-Romera; José C. Riquelme (SOCO (2), 2023)

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)

Advancing unsupervised anomaly detection with normalizing flow and multi-scale ensemble learning. - Miguel Campos-Romero; Manuel Carranza-García; José C. Riquelme (Eng. Appl. Artif. Intell., 2024)

Enhancing smart home appliance recognition with wavelet and scalogram analysis using data augmentation. - Jose L. Salazar-González; José María Luna-Romera; Manuel Carranza-García; Juan Antonio Álvarez-García; Luis Miguel Soria-Morillo (Integr. Comput. Aided Eng., 2024)

A real-time machine learning-based methodology for short-term frequency nadir prediction in low-inertia power systems. - Manuel Jesús Jiménez-Navarro; Jose Miguel Riquelme-Dominguez; Manuel Carranza-García; Francisco M. González-Longatt (Neurocomputing, 2025)