Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Francesco Picetti"'
Publikováno v:
EURASIP Journal on Information Security, Vol 2022, Iss 1, Pp 1-17 (2022)
Abstract Source device identification is an important topic in image forensics since it allows to trace back the origin of an image. Its forensics counterpart is source device anonymization, that is, to mask any trace on the image that can be useful
Externí odkaz:
https://doaj.org/article/1b73b014b2864e9d805011a09712ced2
Autor:
Federico Lombardi, Maurizio Lualdi, Francesco Picetti, Paolo Bestagini, Gerardus Janszen, Luca Angelo Di Landro
Publikováno v:
Remote Sensing, Vol 12, Iss 4, p 717 (2020)
Among all the forensic applications in which it has become an important exploration tool, ground penetrating radar (GPR) methodology is being increasingly adopted for buried landmine localisation, a framework in which it is expected to improve the op
Externí odkaz:
https://doaj.org/article/eaef3f34a8d44f26b191bfba82bdeb22
Autor:
Francesco Picetti
Publikováno v:
Special Topics in Information Technology ISBN: 9783031153730
This brief summarizes some of the main results I obtained during my Ph.D. studies at Politecnico di Milano, under the supervision of Professor Stefano Tubaro. The thesis provides contributions to understanding the advantages, and limitations, of data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed7fa7d1d04a89a93e997afae701f06c
https://doi.org/10.1007/978-3-031-15374-7_12
https://doi.org/10.1007/978-3-031-15374-7_12
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 59:182-195
Buried landmines and unexploded remnants of war are a constant threat for the population of many countries that have been hit by wars in the past years. The huge amount of casualties has been a strong motivation for the research community toward the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e24ec536e1ecf56c1b27dc0a70f8d65f
https://doi.org/10.1109/tgrs.2020.2984951
https://doi.org/10.1109/tgrs.2020.2984951
Publikováno v:
Interpretation. 7:SF15-SF26
The advent of new deep-learning and machine-learning paradigms enables the development of new solutions to tackle the challenges posed by new geophysical imaging applications. For this reason, convolutional neural networks (CNNs) have been deeply inv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bdc026fd30fba43e14af40432ef749b6
https://doi.org/10.1190/int-2018-0232.1
https://doi.org/10.1190/int-2018-0232.1
Publikováno v:
Digital Subsurface Conference in Latin America.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::47a39fe71de1464c1e1449370bcf123e
https://doi.org/10.3997/2214-4609.202181003
https://doi.org/10.3997/2214-4609.202181003
Data interpolation is a fundamental step in any seismic processing workflow. Among machine learning techniques recently proposed to solve data interpolation as an inverse problem, Deep Prior paradigm aims at employing a convolutional neural network t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2344d1937d0643ed94f75cac7f35fa90
Source device identification is an important topic in image forensics since it allows to trace back the origin of an image. Its forensics counterpart is source device anonymization, that is, to mask any trace on the image that can be useful for ident
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b0bbaabfec2d73b7e7e45ad9481c915
http://arxiv.org/abs/2012.03581
http://arxiv.org/abs/2012.03581
Autor:
Paolo Bestagini, Francesco Picetti, Maurizio Lualdi, Federico Lombardi, Luca Di Landro, Gerardus Janszen
Publikováno v:
Remote Sensing; Volume 12; Issue 4; Pages: 717
Remote Sensing, Vol 12, Iss 4, p 717 (2020)
Remote Sensing, Vol 12, Iss 4, p 717 (2020)
Among all the forensic applications in which it has become an important exploration tool, ground penetrating radar (GPR) methodology is being increasingly adopted for buried landmine localisation, a framework in which it is expected to improve the op
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c78b801ce2f8172fea851bce858b6bb