Zobrazeno 1 - 10
of 212
pro vyhledávání: '"FERRAIOLI, Giampaolo"'
Autor:
Alì, Muhammad, Razzano, Francesca, Vitale, Sergio, Ferraioli, Giampaolo, Pascazio, Vito, Schirinzi, Gilda, Ullo, Silvia
Typically, the detection of marine debris relies on in-situ campaigns that are characterized by huge human effort and limited spatial coverage. Following the need of a rapid solution for the detection of floating plastic, methods based on remote sens
Externí odkaz:
http://arxiv.org/abs/2408.10187
Autor:
Yang, Wenyu, Vitale, Sergio, Aghababaei, Hossein, Ferraioli, Giampaolo, Pascazio, Vito, Schirinzi, Gilda
Tropical forests are a key component of the global carbon cycle. With plans for upcoming space-borne missions like BIOMASS to monitor forestry, several airborne missions, including TropiSAR and AfriSAR campaigns, have been successfully launched and e
Externí odkaz:
http://arxiv.org/abs/2403.20273
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing, (2020) 1-14
Deep learning (DL) in remote sensing has nowadays become an effective operative tool: it is largely used in applications such as change detection, image restoration, segmentation, detection and classification. With reference to synthetic aperture rad
Externí odkaz:
http://arxiv.org/abs/2006.09050
SAR images are affected by multiplicative noise that impairs their interpretations. In the last decades several methods for SAR denoising have been proposed and in the last years great attention has moved towards deep learning based solutions. Based
Externí odkaz:
http://arxiv.org/abs/2004.08345
Publikováno v:
2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)
SAR despeckling is a key tool for Earth Observation. Interpretation of SAR images are impaired by speckle, a multiplicative noise related to interference of backscattering from the illuminated scene towards the sensor. Reducing the noise is a crucial
Externí odkaz:
http://arxiv.org/abs/2001.04716
Publikováno v:
2019 Joint Urban Remote Sensing Event (JURSE), Vannes, France, 2019, pp. 1-4
Removing speckle noise from SAR images is still an open issue. It is well know that the interpretation of SAR images is very challenging and despeckling algorithms are necessary to improve the ability of extracting information. An urban environment m
Externí odkaz:
http://arxiv.org/abs/1906.04441
Publikováno v:
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 9494-9497
In SAR domain many application like classification, detection and segmentation are impaired by speckle. Hence, despeckling of SAR images is the key for scene understanding. Usually despeckling filters face the trade-off of speckle suppression and inf
Externí odkaz:
http://arxiv.org/abs/1906.04111
Akademický článek
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Akademický článek
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Publikováno v:
In Computer Methods and Programs in Biomedicine January 2018 153:71-81
