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 Section Staff/Dura

Gabriele Dura



Gabriele is a research grant holder for 5th consecutive year. First four years were focused on industrial research in the Software Defined Radio (SDR) domain, whereas for the last year Gabriele has been focusing on academic research in Cognitive Radio spectrum management aspects.
He is involved in the nSHIELD project, focused on the research of SPD (Security, Privacy and Dependability) in the context of Embedded Systems, with main focus on embedding the Software Defined Radio test bench with various cognitive functionalities.


Ing. Gabriele Dura obtained his master degree in Electronic Engineering in 2008 in University of Genoa with a final mark of 95/110. He has four years of industrial experience, covering several roles related to Software Defined Radio, i.e. Technical manager within a European project concerning the Standardization and the Certification of SDR devices in Europe, Product Manager for the development of a new SDR tactical device, etc.





DITEN - Department of Electrical, Electronic, Telecommunications Engineering and Naval Architecture
University of Genova, Italy
Phone: +39-010-3532212





New accepted papers:

M. Ravanbakhsh, M. Nabi, E. Sangineto, L. Marcenaro, C.S. Regazzoni, and N. Sebe, "Abnormal Event Detection in Videos using Generative Adversarial Nets", 24th IEEE International Conference on Image Processing (ICIP). 17-20 September 2017, Beijing, China

D. Campo, M. Baydoun, L. Marcenaro, and C.S. Regazzoni, "Task-dependent saliency estimation from trajectories of agents in video sequences", 24th IEEE International Conference on Image Processing (ICIP). 17-20 September 2017, Beijing, China

M.O. Mughal, L. Marcenaro, and C.S. Regazzoni, "Energy Detection in Multi-user Relay Networks", Wireless Personal Communications (2017): 1-10

A. Mazzú, P. Morerio, L. Marcenaro, C.S. Regazzoni, "A Cognitive Control-inspired approach to Object Tracking", IEEE Transactions on Image Processing

V. Bastani, L. Marcenaro, C.S. Regazzoni, "Online Nonparametric Bayesian Activity Mining and Analysis From Surveillance Video", IEEE Transactions on Image Processing