Ignacio Aguilera-Martos

According to our database, Ignacio Aguilera-Martos authored at least 13 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

A Survey on Deep Learning-Based Semi-Supervised Semantic Segmentation.

Adrián Peláez-Vegas, Ignacio Aguilera-Martos, Pablo Mesejo, Julián Luengo

ACM Comput. Surv., September, 2026

2025

DenoGrad: Deep Gradient Denoising Framework for Enhancing the Performance of Interpretable AI Models.

J. Javier Alonso-Ramos, Ignacio Aguilera-Martos, Andrés Herrera-Poyatos, Francisco Herrera

CoRR, November, 2025

WinStat: A Family of Trainable Positional Encodings for Transformers in Time Series Forecasting.

Cristhian Moya-Mota, Ignacio Aguilera-Martos, Diego García-Gil, Julián Luengo

Mach. Learn. Knowl. Extr., 2025

Developing Big Data anomaly dynamic and static detection algorithms: AnomalyDSD spark package.

Diego García-Gil, David López, Daniel Argüelles-Martino, Jacinto Carrasco, Ignacio Aguilera-Martos, Julián Luengo, Francisco Herrera

Inf. Sci., 2025

FLEX: Flexible Federated Learning Framework.

Francisco Herrera, Daniel Jiménez-López, Alberto Argente-Garrido, Nuria Rodríguez Barroso, Cristina Zuheros, Ignacio Aguilera-Martos, Beatriz Bello, Mario García-Márquez, María Victoria Luzón

Inf. Fusion, 2025

2024

Local Attention Mechanism: Boosting the Transformer Architecture for Long-Sequence Time Series Forecasting.

Ignacio Aguilera-Martos, Andrés Herrera-Poyatos, Julián Luengo, Francisco Herrera

CoRR, 2024

Local Attention: Enhancing the Transformer Architecture for Efficient Time Series Forecasting.

Ignacio Aguilera-Martos, Andrés Herrera-Poyatos, Julián Luengo, Francisco Herrera

Proceedings of the International Joint Conference on Neural Networks, 2024

2023

Fusing anomaly detection with false positive mitigation methodology for predictive maintenance under multivariate time series.

David López, Ignacio Aguilera-Martos, Marta García-Bárzana, Francisco Herrera, Diego García-Gil, Julián Luengo

Inf. Fusion, December, 2023

Multi-step histogram based outlier scores for unsupervised anomaly detection: ArcelorMittal engineering dataset case of study.

Ignacio Aguilera-Martos, Marta García-Bárzana, Diego García-Gil, Jacinto Carrasco, David López, Julián Luengo, Francisco Herrera

Neurocomputing, August, 2023

TSFEDL: A python library for time series spatio-temporal feature extraction and prediction using deep learning.

Ignacio Aguilera-Martos, Ángel Miguel García-Vico, Julián Luengo, Sergio Damas, Francisco J. Melero, José Javier Valle-Alonso, Francisco Herrera

Neurocomputing, 2023

Revisiting Histogram Based Outlier Scores: Strengths and Weaknesses.

Ignacio Aguilera-Martos, Julián Luengo, Francisco Herrera

Proceedings of the Hybrid Artificial Intelligent Systems - 18th International Conference, 2023

2022

TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning (with Appendices on Detailed Network Architectures and Experimental Cases of Study).

Ignacio Aguilera-Martos, Ángel Miguel García-Vico, Julián Luengo, Sergio Damas, Francisco J. Melero, José Javier Valle-Alonso, Francisco Herrera

CoRR, 2022

2021

Anomaly detection in predictive maintenance: A new evaluation framework for temporal unsupervised anomaly detection algorithms.

Jacinto Carrasco, David López, Ignacio Aguilera-Martos, Diego García-Gil, Irina Markova, Marta García-Bárzana, Manuel Arias-Rodil, Julián Luengo, Francisco Herrera

Neurocomputing, 2021