Zobrazeno 1 - 10
of 140
pro vyhledávání: '"FABRIZIO ARGENTI."'
Autor:
Costanza Cucci, Tommaso Guidi, Marcello Picollo, Lorenzo Stefani, Lorenzo Python, Fabrizio Argenti, Andrea Barucci
Publikováno v:
Heritage Science, Vol 12, Iss 1, Pp 1-15 (2024)
Abstract The study aims at investigating the use of reflectance Hyperspectral Imaging (HSI) in the Visible (Vis) and Near Infrared (NIR) range in combination with Deep Convolutional Neural Networks (CNN) to address the tasks related to ancient Egypti
Externí odkaz:
https://doaj.org/article/00c8394f01de4ace87d1baa7799aac75
Autor:
Fabrizio Argenti, Stefania Bellavia, Marco Fontani, Gabriele Guarnieri, Martino Jerian, Alberto Limone, Simone Rebegoldi
Publikováno v:
IEEE Access, Vol 12, Pp 88303-88321 (2024)
The last years have witnessed significant developments in image acquisition systems and in algorithms for extracting information from them. Nevertheless, in many scenarios, several factors can hinder the recovery of useful data from images. This is e
Externí odkaz:
https://doaj.org/article/05fb8f8db4a8474586a7e7ed6299fe1d
Publikováno v:
IEEE Access, Vol 12, Pp 32334-32348 (2024)
This study employs an unsupervised procedure to spatially decorrelate fully-developed speckle in single-look complex (SLC) synthetic aperture radar (SAR) images. The goal is evaluating the extent to which the spatial correlation of the noise induced
Externí odkaz:
https://doaj.org/article/c8d1a3b79ef547b7bcc816d2e5e28f86
Autor:
Luca Facheris, Andrea Antonini, Fabrizio Argenti, Flavio Barbara, Ugo Cortesi, Fabrizio Cuccoli, Samuele Del Bianco, Federico Dogo, Arjan Feta, Marco Gai, Anna Gregorio, Giovanni Macelloni, Agnese Mazzinghi, Samantha Melani, Francesco Montomoli, Alberto Ortolani, Luca Rovai, Luca Severin, Tiziana Scopa
Publikováno v:
Atmosphere, Vol 14, Iss 3, p 550 (2023)
A novel measurement concept specifically tuned to monitoring tropospheric water vapour’s vertical distribution has been demonstrated on a theoretical basis and is currently under development for space deployment. The NDSA (Normalised Differential S
Externí odkaz:
https://doaj.org/article/5ecf9b6ab16c4276960d11a7b72ed6a1
Autor:
Tommaso Guidi, Lorenzo Python, Matteo Forasassi, Costanza Cucci, Massimiliano Franci, Fabrizio Argenti, Andrea Barucci
Publikováno v:
Algorithms, Vol 16, Iss 2, p 79 (2023)
The objective of this work is to show the application of a Deep Learning algorithm able to operate the segmentation of ancient Egyptian hieroglyphs present in an image, with the ambition to be as versatile as possible despite the variability of the i
Externí odkaz:
https://doaj.org/article/81d1fb3778c8465da02b944034bfb7db
Publikováno v:
IEEE Access, Vol 9, Pp 123438-123447 (2021)
Nowadays, advances in Artificial Intelligence (AI), especially in machine and deep learning, present new opportunities to build tools that support the work of specialists in areas apparently far from the information technology field. One example of s
Externí odkaz:
https://doaj.org/article/5e64781f556441a29bd6b9b7c5421cb5
Autor:
Alessio Martinelli, Monica Meocci, Marco Dolfi, Valentina Branzi, Simone Morosi, Fabrizio Argenti, Lorenzo Berzi, Tommaso Consumi
Publikováno v:
Sensors, Vol 22, Iss 10, p 3788 (2022)
Roads are a strategic asset of a country and are of great importance for the movement of passengers and goods. Increasing traffic volume and load, together with the aging of roads, creates various types of anomalies on the road surface. This work pro
Externí odkaz:
https://doaj.org/article/06e50ac142d34c2ca4f7e69247e813e7
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 20:1-5
Publikováno v:
Remote Sensing, Vol 14, Iss 2, p 414 (2022)
In this paper, we deal with the problem of retrieving maps of tropospheric Water Vapor (WV) concentration by means of a set of Low Earth Orbit (LEO) satellites orbiting in the same plane and along the same direction. It is assumed that a number of mi
Externí odkaz:
https://doaj.org/article/412f1144dd214964b4bef6740e1c8eae
Publikováno v:
Journal of Imaging, Vol 6, Iss 3, p 9 (2020)
Image source forensics is widely considered as one of the most effective ways to verify in a blind way digital image authenticity and integrity. In the last few years, many researchers have applied data-driven approaches to this task, inspired by the
Externí odkaz:
https://doaj.org/article/2f88e0e44ca94d04bd836135233b19a8