• LiDAR as a Geometric Prior: Enhancing Camera Pose Tracking Through High-Fidelity View Synthesis 

  Muñoz-Salinas, Rafael; Liu, Jianheng; Romero Ramírez, Francisco J.; Marín-Jiménez, M.J.; Zhang, Fu (MDPI, 2025)

  This paper presents a robust framework for monocular camera pose estimation by leveraging high-fidelity, pre-built 3D LiDAR maps. The core of our approach is a render-and-match pipeline that synthesizes photorealistic views ...

• Reproducibility Crossroads: Impact of Statistical Choices on Proteomics Functional Enrichment 

  Biełło, Karolina A.; Die, José V.; Amil-Ruiz, Francisco; Fuentes-Almagro, Carlos; Pérez Rodríguez, Javier; Olaya-Abril, Alfonso (MDPI, 2025)

  Quantitative proteomics relies on robust statistical methods for differential expression, critically impacting downstream functional enrichment. This meta-analysis systematically investigated how statistical hypothesis ...

• Design and Validation of PACTUS 2.0: Usability for Neurological Patients, Seniors and Caregivers 

  Sánchez-Gil, Juan J.; Sáez, Aurora; Ochoa Sepúlveda, Juan J.; López Luque, Rafael; Cáceres Gómez, David; Cañete-Carmona, Eduardo (MDPI, 2025)

  Stroke is one of the leading causes of disability worldwide. Its sequelae require early, intensive, and repetitive rehabilitation, but is often ineffective due to a lack of patient motivation. Gamification has been ...

• A probabilistic alert system for extreme wind events prediction using quantile regression ensembles 

  Peláez-Rodríguez, César; Pérez-Aracil, Jorge; Cruz de la Torre, Carlos; Cornejo-Bueno, Laura; Prieto-Godino, Luis; Alexandre-Cortizo, Enrique; Salcedo-Sanz, Sancho (Elsevier, 2026)

  Anticipating and mitigating the impact of extreme wind events is increasingly critical as wind power becomes a central component of modern energy systems. However, existing predictive approaches often struggle to capture ...

• Towards the portability of knowledge in reinforcement learning-based systems for automatic drone navigation 

  Barreiro, José M.; Lara, Juan A.; Manrique, Daniel; Smith, Peter (PeerJ, 2023)

  In the field of artificial intelligence (AI) one of the main challenges today is to make the knowledge acquired when performing a certain task in a given scenario applicable to similar yet different tasks to be performed ...

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