Home Estructura interna Fátima Saiz Álvaro Fátima Saiz Álvaro Directora de Desarrollo de la Sede de Bilbao Doctora en Ingeniería Informática fsaiz@vicomtech.org Publicaciones relacionadas Tesis Doctoral 2022-10-28 A Fast Deep Learning Based Approach for Unsupervised Anomaly Detection in 3D Data Sergio Presa Feijoo Fátima Saiz Álvaro Iñigo Barandiaran Martirena 2022-09-10 Containerized edge architecture for manufacturing data analysis in Cyber-Physical Production Systems Ander García Gangoiti Javier Franco Arroyo Fátima Saiz Álvaro Jairo R. Sánchez Tapia Jan Lukas Bruse 2022-02-01 Photometric Stereo-Based Defect Detection System for Steel Components Manufacturing Using a Deep Segmentation Network Fátima Saiz Álvaro Iñigo Barandiaran Martirena Ander Arbelaiz Aranzasti Manuel Graña Sensors 2021-12-01 An Inspection and Classification System for Automotive Component Remanufacturing Industry Based on Ensemble Learning Fátima Saiz Álvaro Garazi Alfaro Iñigo Barandiaran Martirena Information 2021-09-24 Synthetic Data Set Generation for the Evaluation of Image Acquisition Strategies Applied to Deep Learning Based Industrial Component Inspection Systems Fátima Saiz Álvaro Garazi Alfaro García Iñigo Barandiaran Martirena Sara García Torres María del Puy Carretero Carrasco Manuel Graña 2021-07-09 Generative Adversarial Networks to Improve the Robustness of Visual Defect Segmentation by Semantic Networks in Manufacturing Components Fátima Saiz Álvaro Garazi Alfaro García Iñigo Barandiaran Martirena Manuel Graña Applied Sciences (Switzerland) 1 2 09.02.2023 Artificial Intelligence for Advanced Manufacturing Quality Control Fátima Saiz Álvaro