19 citations · 37 across the 5 of their papers we have counts for
6 papers
Data-Driven Surrogate-Model for Real-Time Loads Prediction in Floating Wind Farms
Federico Bellini, Majid Ebrahimi, Alessandro Fontanella +4
This work presents a data-driven load-surrogate modelling framework for real-time control of floating offshore wind farms. The proposed methodology uses mid-fidelity simulations pe…
Challenges of building medical image datasets for development of deep learning software in stroke
Alessandro Fontanella, Wenwen Li, Grant Mair +7
Despite the large amount of brain CT data generated in clinical practice, the availability of CT datasets for deep learning (DL) research is currently limited. Furthermore, the dat…
Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain Images
Alessandro Fontanella, Grant Mair, Joanna Wardlaw +2
Segmentation masks of pathological areas are useful in many medical applications, such as brain tumour and stroke management. Moreover, healthy counterfactuals of diseased images c…
ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging
Alessandro Fontanella, Antreas Antoniou, Wenwen Li +4
In some medical imaging tasks and other settings where only small parts of the image are informative for the classification task, traditional CNNs can sometimes struggle to general…
Fault Detection of the Mooring system in Floating Offshore Wind Turbines based on the Wave-excited Linear Model
Yichao Liu, Alessandro Fontanella, Ping Wu +2
Floating Offshore Wind Turbines (FOWTs) are more prone to suffer from faults and failures than bottom-fixed counterparts due to the severe wind and wave loads typical of deep water…
Feedforward control for wave disturbance rejection on floating offshore wind turbines
Mees Al, Alessandro Fontanella, Daan van der Hoek +3
Floating offshore wind turbines allow wind energy to be harvested in deep waters. However, additional dynamics and structural loads may result when the floating platform is being e…