Zobrazeno 1 - 10
of 87
pro vyhledávání: '"Nicola, Acito"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 4379-4391 (2024)
Satellite-based remote sensing images are essential for Earth surface analysis, serving diverse purposes in both civilian and military domains. Satellite images are used for analysis and decision making and are considered a reliable source of informa
Externí odkaz:
https://doaj.org/article/5039f9ff6ef14f1fa97672fca13c8a91
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 62-79 (2022)
This article deals with the problem of improving the spatial resolution of hyperspectral (HS) data from the PRecursore IperSpettrale della Missione Applicativa (PRISMA) mission. For this purpose, higher spatial resolution data from the Sentinel-2 (S2
Externí odkaz:
https://doaj.org/article/d7da76e2d13f4c3f8f9f2da470ec66c2
Publikováno v:
Sensors, Vol 23, Iss 14, p 6334 (2023)
Moving target detection (MTD) is a crucial task in computer vision applications. In this paper, we investigate the problem of detecting moving targets in infrared (IR) surveillance video sequences captured using a steady camera in a maritime setting.
Externí odkaz:
https://doaj.org/article/05c28d41c4824036a40cc24311ef9b87
Publikováno v:
Remote Sensing, Vol 13, Iss 15, p 2967 (2021)
Atmospheric compensation (AC) allows the retrieval of the reflectance from the measured at-sensor radiance and is a fundamental and critical task for the quantitative exploitation of hyperspectral data. Recently, a learning-based (LB) approach, named
Externí odkaz:
https://doaj.org/article/888853c41e994a2591fc49f179e06caa
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-15
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::58b1fd58e9cebf7ff4a91be45d89c93e
https://doi.org/10.1109/tgrs.2022.3206453
https://doi.org/10.1109/tgrs.2022.3206453
Autor:
Nicola Acito
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-15
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24105210b36dbacb9bcc54a22e4f6804
https://doi.org/10.1109/tgrs.2021.3099957
https://doi.org/10.1109/tgrs.2021.3099957
Publikováno v:
Electro-Optical Remote Sensing XVI.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b7dea763bfc4981b6c2b0b5f839e4285
https://doi.org/10.1117/12.2636135
https://doi.org/10.1117/12.2636135
Autor:
Lt. Osvaldo Pulpito, Nicola Acito, Marco Diani, Giovanni Corsini, Raffaele Grasso, Gabriele Ferri, Alberto Grati, Kevin Le Page, Konstantina Bereta, Dimitris Zissis
Publikováno v:
2022 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::13e13edef1c776cbac44e6ba32997f51
https://doi.org/10.1109/metrosea55331.2022.9950885
https://doi.org/10.1109/metrosea55331.2022.9950885
Autor:
Lt. Lorenzo Bazzarello, Lt. Osvaldo Pulpito, Lt. Francesco Cannarsa, Matteo Bresciani, Riccardo Costanzi, Nicola Acito, Marco Diani, Giovanni Corsini, Andrea Caiti
Publikováno v:
2022 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::534e440e3b7f43dc8183e0437182e7cf
https://doi.org/10.1109/metrosea55331.2022.9950937
https://doi.org/10.1109/metrosea55331.2022.9950937
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 59:4218-4232
In this work, we deal with the problem of atmospheric compensation (AC) of hyperspectral data collected in the visible and near-infrared (VNIR) spectral range. We propose the “learning-based” approach which uses artificial intelligence algorithms
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ffdb9988f90aec65c354c44aa28da9c
https://doi.org/10.1109/tgrs.2020.3016094
https://doi.org/10.1109/tgrs.2020.3016094