The "5G Italy" initiative reaches its 5th edition. The international conference promoted and organised by the Italian National Inter-University Consortium for Telecommunications – CNIT (Consorzio Nazionale Interuniversitario per le Telecomunicazioni) is once again the most significant event in Italy on 5G and its several application areas.

The fifth edition of 5G Italy – Towards the Telecoms of the future –  will cover the research, development, and implementation activities currently under way in Italy and the rest of the World and will also feature the projects linked to the National Recovery and Resilience Plan – NRRP (Piano Nazionale di Ripresa e Resilienza, PNRR), allocating major investments for the digitalisation of the Country.

In this transition process, 5G will act as one of the connecting points for electronic communications and will be a key factor to boost national economy, as well as drive economic growth. In this complicated and challenging historical period, 5G will play a more and more relevant role for its industrial and social applications, but also in fields such as services, businesses, and Public Administrations.

5G Italy will also be a great networking opportunity: a strategic meeting-point for businesses, public entities, the academic world and decision-makers.

Finally, as usual, the event will feature scientific sessions and the PhD School, which will take place in parallel with the main Conference.

Both the main Conference and especially the scientific sessions will deal with the evolution of 5G towards 6G, and new mobile or fixed network architectures.

For more information, visit:


The 7th International Conference on Computer Vision & Image Processing (CVIP-2022), a premier annual conference focused on Computer Vision and Image Processing will be held on November 04-06, 2022. CVIP-2022 conference is being organized by Visvesvaraya National Institute of Technology Nagpur (VNIT Nagpur), Maharashtra, INDIA. CVIP 2022 is endorsed by the International Association for Pattern Recognition "IAPR". The proceedings of CVIP will be published in Springer Series on Communications in Computer and Information Science (CCIS) Springer.

The conference website is available at: 

Prof. Fabio Dell'Acqua will be a keynote speaker at the conference.

The manuscript "Correlation between weather and signal strength in LoRaWAN networks: An extensive dataset" has been accepted for publication as a dataset article in Computer Networks.
The authors would like to thank Marco Franchi and all the staff of Sitip Srl (Bondeno, Mantova) for providing all the hardware and the support needed for the tests.
In the following you may find the abstract, and the IRIS link to the preprint manuscript.

New paper: Yanzi Shi, Jiaojiao Li, Yunsong Li, Paolo Gamba, Hyperspectral Target Detection Using a Bilinear Sparse Binary Hypothesis Model, IEEE Transactions on Geoscience and Remote Sensing

Abstract: The binary hypothesis testing (BHT) is one of the most important models in hyperspectral target detection (HTD). However, this model is generally based on linear mixture model (LMM), and might be inaccurate to reflect target and background characterizations in some scenes. This paper presents a bilinear sparse target detector (BSTD) by applying bilinear sparse mixture model (BSMM) to a popular BHT-based detection algorithm termed adaptive matched subspace detector (AMSD), which takes bilinear target-background interaction and sparse abundance into account. Moreover, as AMSD relies heavily on background subspace, we design a robust background subspace construction method. Specifically, we first classify each pixel into noise, border, or other particular instances according to its density, which is measured by jointly spatial-spectral distance. With the coarse classification map, a class-guided automatic background generation (CABG) process is introduced to reliably generate pure background samples. Detection statistics and component analysis on five real-world hyperspectral images verify the effectiveness of our BSTD method.

The pdf of the paper is available at

David Marzi and Paolo Gamba have just published a new paper, entitled "Inland Water Body Mapping Using Multitemporal Sentinel-1 SAR Data", in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS).

This work addresses the importance of water bodies monitoring and mapping using SAR satellite data in the context of climate change studies. Indeed, analyzing changes over time of this precious land cover type in terms of extent and/or transition towards other classes, is essential for the characterization of climate and, thus, for the whole climate change community.

By leveraging the astonishing computational power of Google EarthEngine, we developed a fully automated system exploiting Sentinel-1 aimed at analyzing wide geographical areas located anywhere in the World. It generates high-resolution water bodies maps by applying a totally unsupervised approach to sequences of Sentinel-1 SAR data in just a matter of minutes.

The journal is 100% open access, which means that the whole article content is freely available and downloadable at this link