Quality In / Quality Out: Data quality more relevant than model choice in anomaly detection with the UGR'16. - José Camacho 001; Katarzyna Wasielewska; Pablo Espinosa; Marta Fuentes-García (NOMS, 2023)

SIMAGRO: A Prototype for Network Anomaly Detection in Agrifood IoT Environments. - Roberto Magán-Carrión; Marta Fuentes-García; Celia Fernández; Patricia Maldonado-Mancilla (WF-IoT, 2023)

Quality In / Quality Out: Assessing Data quality in an Anomaly Detection Benchmark. - José Camacho 001; Katarzyna Wasielewska; Marta Fuentes-García; Rafael Rodríguez-Gómez (CoRR, 2023)