Iván Sevillano-García

According to our database, Iván Sevillano-García authored at least 11 papers between 2020 and 2026.

Collaborative distances:

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

2026

X-SHIELD: Regularization for explainable Artificial Intelligence.

Iván Sevillano-García, Julián Luengo, Francisco Herrera

Mach. Intell. Res., June, 2026

STOOD-X: Explainable out-of-distribution detection via nonparametric statistical testing on large-scale datasets.

Iván Sevillano-García, Julián Luengo, Francisco Herrera

Pattern Recognit., 2026

2025

Explainability in Context: A Multilevel Framework Aligning AI Explanations with Stakeholder with LLMs.

Marilyn Bello, Rafael Bello, María-Matilde García, Ann Nowé, Iván Sevillano-García, Francisco Herrera

CoRR, June, 2025

STOOD-X methodology: using statistical nonparametric test for OOD Detection Large-Scale datasets enhanced with explainability.

Iván Sevillano-García, Julián Luengo, Francisco Herrera

CoRR, April, 2025

2024

SHIELD: A regularization technique for eXplainable Artificial Intelligence.

Iván Sevillano-García, Julián Luengo, Francisco Herrera

CoRR, 2024

2023

REVEL Framework to Measure Local Linear Explanations for Black-Box Models: Deep Learning Image Classification Case Study.

Iván Sevillano-García, Julián Luengo, Francisco Herrera

Int. J. Intell. Syst., 2023

Low-Impact Feature Reduction Regularization Term: How to Improve Artificial Intelligence with Explainability.

Iván Sevillano-García, Julián Luengo, Francisco Herrera

Proceedings of the Joint Proceedings of the xAI-2023 Late-breaking Work, 2023

Optimizing LIME Explanations Using REVEL Metrics.

Iván Sevillano-García, Julián Luengo, Francisco Herrera

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

2022

A tutorial on the segmentation of metallographic images: Taxonomy, new MetalDAM dataset, deep learning-based ensemble model, experimental analysis and challenges.

Julián Luengo, Raúl Moreno, Iván Sevillano-García, David Charte, Adrián Peláez-Vegas, Marta Fernández-Moreno, Pablo Mesejo, Francisco Herrera

Inf. Fusion, 2022

2021

Slicer: Feature Learning for Class Separability with Least-Squares Support Vector Machine Loss and COVID-19 Chest X-Ray Case Study.

David Charte, Iván Sevillano-García, María Jesús Lucena-González, José Luis Martín-Rodríguez, Francisco Charte, Francisco Herrera

Proceedings of the Hybrid Artificial Intelligent Systems - 16th International Conference, 2021

2020

COVIDGR Dataset and COVID-SDNet Methodology for Predicting COVID-19 Based on Chest X-Ray Images.

Siham Tabik, Anabel Gómez-Ríos, J. L. Martín-Rodríguez, I. Sevillano-García, Manuel Rey-Area, David Charte, Emilio Guirado, Juan-Luis Suárez, Julián Luengo, M. A. Valero-González, P. García-Villanova, Eulalia Olmedo-Sánchez, Francisco Herrera

IEEE J. Biomed. Health Informatics, 2020