Exhibitors 2021
- FASHION & WEARABLES
- INTERNET OF THINGS
- PRODUCT DESIGN
- 3D PRINTING
- 3D SCANNING
- ART
- ARTIFICIAL INTELLIGENCE
- BIOLOGY
- EDUCATION
- HACKS
- KIDS & EDUCATION
- OPEN SOURCE
- ROBOTICS
- MUSIC & SOUND
- ARTISANS & NEW CRAFT
- RECYCLING & UPCYCLING
- STEAM PUNK
- GAMES
- SCIENCE
- YOUNG MAKERS (< 18)
- FOOD & AGRICULTURE
- CIRCULAR ECONOMY
- AEROSPACE
- HOME AUTOMATION
- NEW MANUFACTURING
- STARTUP
- WELLNESS & HEALTHCARE
- ENERGY & SUSTAINABILITY
- FABRICATION
- INDUSTRIAL AUTOMATION
- RETROCOMPUTING
- DRONES
- CULTURAL HERITAGE
- VIRTUAL REALITY
Informazioni implicite ed esplicite nei documenti digitali
Digital documents can contain sensitive data both explicitly (e.g., personal data) and implicitly (e.g., metadata showing the author of the text). It is important to remove any sensitive data before the publication of the documents. To this end, Unibas (in collaboration with Multipartner spa) has started a research project about the use of artificial intelligence to find and remove sensitive data from digital documents in an automatic manner. The presented solution relies on machine learning and graph theory based algorithms.
Domenico Daniele Bloisi in collaborazione con Multipartner spa
Dr Bloisi is assistant professor (tenure track) with the Department of Mathematics, Computer Science, and Economics at the University of Basilicata. He received his PhD, M.Sc., and B.Sc. degrees in Computer Engineering from Sapienza University of Rome in 2010, 2006 and 2004, respectively. Dr Bloisi collaborates with the SPQR robot soccer team (http://spqr.diag.uniroma1.it/), which is involved in the RoboCup competitions, and works on automatic methods for medical image segmentation for melanoma cancer prevention in collaboration with the medical staff of the Istituto Dermopatico dell'Immacolata (IDI-IRCCS).
Additional information can be found at https://web.unibas.it/bloisi/
