2 citations · 3 across the 5 of their papers we have counts for
5 papers
Adaptive sampling using variational autoencoder and reinforcement learning
Adil Rasheed, Mikael Aleksander Jansen Shahly, Muhammad Faisal Aftab
Compressed sensing enables sparse sampling but relies on generic bases and random measurements, limiting efficiency and reconstruction quality. Optimal sensor placement uses histor…
Predictive Digital Twin for Condition Monitoring Using Thermal Imaging
Daniel Menges, Florian Stadtmann, Henrik Jordheim +1
This paper explores the development and practical application of a predictive digital twin specifically designed for condition monitoring, using advanced mathematical models and th…
Diagnostic Digital Twin for Anomaly Detection in Floating Offshore Wind Energy
Florian Stadtmann, Adil Rasheed
The demand for condition-based and predictive maintenance is rising across industries, especially for remote, high-value, and high-risk assets. In this article, the diagnostic digi…
Digital Twin for Wind Energy: Latest updates from the NorthWind project
Adil Rasheed, Florian Stadtmann, Eivind Fonn +12
NorthWind, a collaborative research initiative supported by the Research Council of Norway, industry stakeholders, and research partners, aims to advance cutting-edge research and…
Data Integration Framework for Virtual Reality Enabled Digital Twins
Florian Stadtmann, Hary Pirajan Mahalingam, Adil Rasheed
Digital twins are becoming increasingly popular across many industries for real-time data streaming, processing, and visualization. They allow stakeholders to monitor, diagnose, an…