Research · 02
Sensor and Data Fusion
Data and information fusion is a long-standing focus of the laboratory. Methods range from classical estimation and Bayesian approaches to ordered weighted averaging, evidential reasoning and learned fusion models.
Applications include wearable and body-worn sensing, industrial measurement, biomedical decision support and multi-source environmental inference.
- Multi-sensor fusion
- OWA operators
- Estimation
- Evidence theory
Related Publications
All publications →2026
CB-OWL-ViT: A Multimodal Cost-Effective Framework for Contagious Disease Monitoring
Mohammad Fatahi, Danial Sadrian Zadeh, Ali Noormohammadi-Asl, Behzad Moshiri, Otman Basir, Ebrahim Navid Sadjadi, Jesús García-Herrero, José M. Molina
Mathematics
2025
Enhancing Surgical Skill Assessment Through Soft and Hard Data Fusion Using Dempster–Shafer Theory and Large Language Models
Arash Iranfar, Elahe Radmanesh, Behzad Moshiri, Mohammad Reza Nayeri, Hamid D. Taghirad
IEEE Access
2025
Fault Detection and Severity Classification of Inter-turn Short-Circuit Faults in PMSMs Using a Combination of Projection-Based Support Vector Machine and Bayesian Neural Network
Abbas Darvishi, Seyed Mohsen Seyed Moosavi, Ebrahim Aghajari, Behzad Moshiri
OICC Press Journals
2025
Intelligent fault diagnosis based on similarity analysis using generative model and multi-sensor fusion in industrial processes
Amir Shirshahi, Behzad Moshiri, Mahdi Aliyari-Shoorehdeli
Process Safety and Environmental Protection
2023
Supervised learning for more accurate state estimation fusion in IoT-based power systems
Danial Sadrian Zadeh, Behzad Moshiri, Moein Abedini, Josep M. Guerrero
Information Fusion