12 citations · 42 across the 9 of their papers we have counts for
3 papers · 1 filter
An Improved Anomaly Detection Model for Automated Inspection of Power Line Insulators
Laya Das, Blazhe Gjorgiev, Giovanni Sansavini
Inspection of insulators is important to ensure reliable operation of the power system. Deep learning is being increasingly exploited to automate the inspection process by leveragi…
There is more to graphs than meets the eye: Learning universal features with self-supervision
Laya Das, Sai Munikoti, Nrushad Joshi +1
We study the problem of learning features through self-supervision that are generalisable to multiple graphs. State-of-the-art graph self-supervision restricts training to only one…
Uncertainty-aware deep learning for digital twin-driven monitoring: Application to fault detection in power lines
Laya Das, Blazhe Gjorgiev, Giovanni Sansavini
Deep neural networks (DNNs) are often coupled with physics-based models or data-driven surrogate models to perform fault detection and health monitoring of systems in the low data…