A Study on the Noise Label Influence in Boosting Algorithms: AdaBoost, GBM and XGBoost. - Anabel Gómez-Ríos; Julián Luengo; Francisco Herrera (HAIS, 2017)

Towards highly accurate coral texture images classification using deep convolutional neural networks and data augmentation. - Anabel Gómez-Ríos; Siham Tabik; Julián Luengo; A. S. M. Shihavuddin; Bartosz Krawczyk; Francisco Herrera (Expert Syst. Appl., 2019)

Coral species identification with texture or structure images using a two-level classifier based on Convolutional Neural Networks. - Anabel Gómez-Ríos; Siham Tabik; Julián Luengo; A. S. M. Shihavuddin; Francisco Herrera (Knowl. Based Syst., 2019)

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; et al. (IEEE J. Biomed. Health Informatics, 2020)

A robust approach for deep neural networks in presence of label noise: relabelling and filtering instances during training. - Anabel Gómez-Ríos; Julián Luengo; Francisco Herrera (CoRR, 2021)