Exhibitors 2023
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Approcci di Machine Learning per la classificazione di immagini dermoscopiche
Skin cancer is one of the most common cancers in the world with a high mortality rate. Early identification and diagnosis of skin lesions is essential to determine the best treatment for the patient and to increase the survival rate in the case of cancerous lesions. Diagnosis of this disease is conducted manually by more or less experienced dermatologists, but it proves to be time consuming and difficult. Machine-learning and deep-learning approaches have been developed to overcome these issues and support dermatologists, in order to make this procedure much easier, faster, and more accurate.
Fabrizio Frezza, Carmen Cantisani, Flavia Grignaffini, Maurizio Troiano, Lorenzo Piazzo
Fabrizio Frezza received his Master degree in Electronic Engineering (cum laude) in 1986 and his Ph.D. in Applied Electromagnetics and Electrophysical Sciences in 1991 from the University of Rome "La Sapienza."
In 1986 he began his work at the Department of Electronics, University of Rome "La Sapienza," where he was Researcher of Electromagnetic Fields from 1990 to 1998, Lecturer from 1994 to 1998, Associate Professor from 1998 to 2004, and Full Professor since 2005.
His research activities have involved waveguides, antennas and electromagnetic resonators; mathematical and numerical methods, electromagnetic scattering, optics, free electromagnetic propagation, heating of thermonuclear plasmas, anisotropic materials, artificial materials and metamaterials, plasmonics, biomedical applications, applications to cultural and environmental heritage, applications of artificial intelligence to sensing and diagnostics, applications of magnetic resonance, electrical transmission lines, electromagnetic compatibility, spectroscopy, applications to terahertz, technology transfer, history of science and technology.
Fabrizio Frezza is a Member of Sigma Xi and a Senior Member of IEEE, OSA and URSI. He is also a member of the Quadrato della Radio Association.
