Projects

Showing 1 - 6 results of 6

ATARI aims to strengthen the expertise and improve the research profile of ECoE, through the collaboration with three research institutes and one SME in the field of atmospheric and solar radiation modelling and remote sensing. The collaborating institutions consist of highly experienced developers of global use models, linked with bodies such as the world meteorological...

Atmospheric dust gives us one of the most visible and detectable aspects of transboundary transport of atmospheric constituents, impacting visibility, radiation and climate. What is less evident are its impacts on health, transportation and energy production.

Atmospheric dust is not fully understood at the fundamental level and models fail to fully...

Cloud, aerosols and their interactions are key regulators of climate. However, uncertainties in the magnitude of the net cooling impact of aerosols on climate and in the cloud response to evolving anthropogenic emissions and climate change induced feedbacks on natural emissions are major challenges that limit our understanding of how global and regional climate, including...

Monitoring the composition of the atmosphere is a key objective of the European Union's flagship Space programme, Copernicus. The Copernicus Atmosphere Monitoring Service (CAMS) provides free and continuous data and information on atmospheric composition and the CAMS Service Evolution (CAMEO) project will enhance the quality and efficiency of the CAMS service and help CAMS to...

Ultrasound imaging can be deeply enhanced by means of algorithms developed in the field of geophysical imaging. Such algorithms, based upon adjoint-state modelling and iterative optimization, provide quantitative images of human tissue with very high resolution. At present time, suchimages can only be attained by means of high-performance computing and using specific...

The increasing amount and availability of collected data (cancer imaging) and the development of novel technological tools based on Artificial Intelligence (AI) and Machine Learning (ML), provide unprecedented opportunities for better cancer detection and classification, image optimization, radiation reduction, and clinical workflow enhancement. The 42-month INCISIVE project...