19th-23rd May 2025
APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN REMOTE SENSING-BASED METHODS FOR THE ESTIMATION OF GEOPHYSICAL PARAMETERS OF THE EARTH SURFACES
Given the current interest in artificial intelligence and its applications, the Institute of Applied Physics of the CNR (IFAC-CNR) together with the Microwave Remote Sensing Center (Ce.Te.M.), with the support of IEEE and its Chapters (in particular GRS29-CNI and GRS29 SI) and the Patronage of the Italian Society of Remote Sensing (AIT) organizes a School on the applications of remote sensing techniques to the Earth surfaces.
The school will be held from 19 to 23 May 2025 at the Academy of Sciences and Drawing (in via Orsanmichele, 4, in Florence). The program includes the participation of the main Italian researchers and university professors who deal with AI. The courses will focus on the following topics: • An overview of Artificial Intelligence Techniques and Applications:
- An overview of Artificial Intelligence Techniques and Applications;
- Once Upon a Time there was the Bayesian Approach of Parameter Retrieval;
- Machine Learning Applications for Remote Sensing of Soil Moisture, Vegetation Biomass and Snow;
- Physics-Based AI in Earth Observation;
- Deep Learning Methods for Characterizing Urban Areas Using Radar and Optical sensors;
- Quantum Machine Learning Applied to EO;
- Snow Cover Fraction Mapping from Optical Imagery: a Progression from NDSI Thresholding to Nonlinear Machine Learning Based Unmixing;
- Marine Macroalgae Extraction Using Remote Sensing and AI.
Applications for participation must arrive by April 15th to this email address: s.paloscia@ifac.cnr.it by filling out the form at the link http://cetem.org/it/centro-di-telerilevamento-microonde/attivita/eventi/scuola-intelligenza-artificiale/.
Participation fee is €250 and must be paid upon confirmation of registration (by April 30th). Given the limited number of places, acceptance of registration beyond this date cannot be guaranteed.
The organizers
Simonetta Paloscia (IFAC-CNR),
Simone Pettinato (IFAC-CNR),
Emanuele Santi (IFAC-CNR).
