Tesis Doctorales
- Cesar Montenegro Portillo "Contributions to Natural Languaje Processing and Hierarchical Classification" UPV/EHU. 2024
- Onintze Zaballa Larumbe "Unsupervised learning approaches for disease progression modeling" UPV/EHU. 2024
- Pendar Alirezazadeh "Angular Margin-bases Softmax Losses: Toward Discriminative Metric Learning" UPV/EHU. 2024
- Daniel Franco Barranco "Deep Learning for Bioimage Analysis: novel user and developer-oriented approaches" UPV/EHU. 2024
- Jingjun Bi "CONTRIBUTION TO GRAPH-BASED SEMI-SUPERVISED DEEP LEARNING" UPV/EHU. 2024
- Alberto Díez Olivan "Técnicas bio-inspiradas para el diseño y aplicación de modelos cognitivos en la industria digital" UPV/ehu. 2024
- Danyang Sun "Contribution to Data Augmentation for Image Classification and Segmentation" UPV/EHU. 2024
- Goizalde Badiola Zabala "Contributions to COVID-19 pandemic data analysis" UPV/EHU. 2024
- Francisco Robledo Relaño "Advanced Reinforcement Learning Algorithms for Multi-Armed Bandit Problems" UPV/EHU. 2024
- Jon Kerexeta Sarriegi "Combining visual analytics, data mining, and artificial intelligence methods" UPV/EHU. 2024
- Jose Luis Outon Mendez "Soluciones innovadoras basadas en manipuladores móviles para el nuevo paradigma de fabricación flexible en el marco de la Industria 4.0" UPV/EHU. 2024
- Jon Vadillo Jueguen "Broadening the Horizon of Adversarial Attaks in Deep Learning" UPV/EHU. 2023
- Asier Izquierdo Perez "Intelligent road lane mark extraction using a Mobile Mapping System" UPV/EHU. 2023
- Fátima Aurora Sáiz Álvaro "Artificial Intelligence for advanced manufacturing quality" UPV/EHU. 2023
- Itsaso Rodriguez Moreno "Machine Learning Approaches to Video Activity Recognition: from Computer Vision to Signal Processing" UPV/EHU. 2023
- David Montero Martin "Optimization for Deep Learning Systems Applied to Computer Vision" UPV/EHU. 2023
- Ander Iriondo Azpiri "Advances in flexible manipulation through the application of AI-based techniques" UPV/EHU. 2023
- Josu Ircio Fernandez "Anomaly Detection in Multivariate Time Serie" UPV/EHU. 2023
- Ricardo Muñoz Cancino "On the use of multi-sensor digital traces to discover spatio-temporal human behavioral pattems" UPV/EHU. 2023
- David Velásquez Rendón "Machine learning based anomaly detection for industry 4.0 systems" UPV/EHU. 2023
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