Ongoing Projects
Face:LIFT - The Face:LIFT project is funded under the MCST Fusion Technology Development Programme (€200,000) involves the development of software that is ably to synthesize a face from a text description.
WAter Resource Management platform using Earth Observation (WARM-EO) - The WARM-EO project funded under the National Space Research Fund Programme (€150,000) involves the development of an optical super-resolution algorithm to improve the resolution of Sentinel-2 images and use it to develop a high resolution evapotranspiration model of the whole country. The output of this project will be used to estimate the amount of irrigation water used in agricultural fields.
BIOremediation for coastal debris in BLUE Flag beach and in a Maritime Protected Area (BioBlu) - The BIOBLU project is funded through the Interreg Italia-Malta European Regional Development Fund (total of €1,650,052) and will aim at mitigating the effects of plastic and microplaslic debris which litter our seas and beaches. Deep learning will be used to detect and localise litter remotely, which will enable automatic litter connection using a robot.
Coastal SAGE - The “Coastal Satellite Assisted Governance (tools, techniques, models) for Erosion” (Coastal SAGE) funded under the National Space Research Fund Programme (€150,000) project will use image processing and deep learning techniques to address two key aspects of the PSI pipeline: denoising of interferometric phase and phase unwrapping.
VoLARe - The VoLARe project funded under the MCST Fusion Technology Development Programme (€200,000) involves the design and development of a low-cost video light field capturing prototype which aims to reduce the number of cameras by a factor of nine thus reducing the throughput down to 30Gbps. Our partners are Stargate Studios Malta, a video production and visual effects company that will use the developed video light field capturing system in a production.
Face Image Restoration using Deep-Learning project (Deep-FIR) - The Face Image Restoration using Deep-Learning project (Deep-FIR) funded under the MCST Fusion Technology Development Programme (€201,727) aims to use advanced Artificial Intelligence techniques to improve the quality of facial images from very-low resolution quality images and videos.
Past Projects
Satellite Training and NETworking (SATINET) - The SATINET project (€50,000) was a collaborative project with the French Space Agency CNES and aims to use deep learning to derive the digital elevation model automatically from a pair of satellite images. (2019-2021)
Automated SEgmentation of Microtompgraphy Images (ASEMI) - The project is a collaborated with ESRF to develop and use artificial intelligence techniques to automatically perform this 3D sementation process. Following the principles of “Open Innovation, Open Science, Open to the World”, the developed algorithms, data sets, and results will be made available to the general public. This project has received funding from the ATTRACT project funded by the EC (€100,000) under Grant Agreement 777222. (2019-2020)
Forensic against Child Sexual Exploitation (4NSEEK) - The 4NSEEK project is an H2020 funded project which involves the development of tools that can be used by police agencies to aid investigations related to child abuse. (2019-2021)
SATellite data Fusion and Imaging Resolution Enhancement (SAT-FIRE) - The SAT-FIRE project funded under the National Space Research Fund Programme (€150,000) involves thed development of thermal image super-resolution of Sentinel-3 images which improve the resolution of thermal images by a factor of 5. The resulting super-resolved thermal images were used to validate and improve hydrodynamical models covering the central Mediterranean and the Maltese Islands, providing four-day forecasts. (2019-2020)
