Zobrazeno 1 - 10
of 173
pro vyhledávání: '"R. Pierdicca"'
Autor:
M. Balestra, R. Pierdicca, L. Cesaretti, G. Quattrini, A. Mancini, A. Galli, E. S. Malinverni, S. Casavecchia, S. Pesaresi
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-1-W1-2023, Pp 33-40 (2023)
Satellite remote sensing has gained a key role for vegetation mapping distribution. Given the availability of multi-temporal satellite data, seasonal variations in vegetation dynamics can be used trough time series analysis for vegetation distributio
Externí odkaz:
https://doaj.org/article/e22e13c92ec34929a9262884f4611e6f
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-1-W1-2023, Pp 1089-1096 (2023)
Automated tree classification from unmanned aerial vehicle (UAV) images is a challenging task with several applications in forest management and conservation. In this study, we propose UAV4Tree a Deep Learning based system that automatically classifi
Externí odkaz:
https://doaj.org/article/1b1570cd50164cca905c5c56f24d263c
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-M-1-2023, Pp 207-214 (2023)
Deep Learning has been pivotal in many real-world applications (e.g., autonomous driving, medicine and retail). With the wide availability of consumer-grade depth sensors, acquiring 3D data has become more affordable and effective, and many 3D datase
Externí odkaz:
https://doaj.org/article/24c0ab24142f45c2b1977bb13bc79844
Autor:
D. Abate, A. Agapiou, K. Toumbas, A. Lampropoulos, K. Petrides, R. Pierdicca, M. Paolanti, F. Di Stefano, A. Felicetti, E. S. Malinverni, P. Zingaretti
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-M-2-2023, Pp 3-10 (2023)
The use of artificial intelligence (AI) has the potential to be highly effective in detecting and monitoring illegal trafficking of cultural heritage (CH) goods through image classification techniques, particularly on online marketplaces where the tr
Externí odkaz:
https://doaj.org/article/cfa910f351804e4695de0bf7d2878ba1
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-M-2-2023, Pp 155-162 (2023)
3D documentation methods for Digital Cultural Heritage (DCH) domain is a field that becomes increasingly interdisciplinary, breaking down boundaries that have long separated experts from different domains. In the past, there has been an ambiguous cla
Externí odkaz:
https://doaj.org/article/e1927e2831ee49f8b4b6fbd97e9a8100
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-M-2-2023, Pp 1225-1232 (2023)
The documentation of Cultural Heritage, and in particular architecture, is nowadays conducted with a combination of several geomatic techniques. Most of them relies on the exploitation of 3D point cloud, which is the state of art data to produce almo
Externí odkaz:
https://doaj.org/article/75fc89ddc5fb4d26bba3a6643c04dbce
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-1-W1-2023, Pp 131-138 (2023)
In this contribution a point cloud classification in an urban context has been presented. The aim of the work is to test a semi-automatic classification approach and to verify its usefulness in the scan-to BIM process, and to validate how much it is
Externí odkaz:
https://doaj.org/article/23ae592ecfc64d759a3a77e3f69cb8d1
Autor:
X. Liang, Y. Wang, F. Pirotti, J. C. White, F. Faßnacht, M. T. Melis, W. Gong, M. Yamashita, J. Hernandez, M. Mokroš, M. Campos, R. Pierdicca
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-1-W2-2023, Pp 2003-2003 (2023)
Externí odkaz:
https://doaj.org/article/7dc5f44f97da46efb769bc7aa7ef574a
Autor:
R. Pierdicca, M. Paolanti
Publikováno v:
Geoscientific Instrumentation, Methods and Data Systems, Vol 11, Pp 195-218 (2022)
Researchers have explored the benefits and applications of modern artificial intelligence (AI) algorithms in different scenarios. For the processing of geomatics data, AI offers overwhelming opportunities. Fundamental questions include how AI can be
Externí odkaz:
https://doaj.org/article/09a193fdd2f34ee380ef7b8828b18d81
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-2-2022, Pp 317-324 (2022)
In the geomatics domain the use of deep learning, a subset of machine learning, is becoming more and more widespread. In this context, the 3D semantic segmentation of heritage point clouds presents an interesting and promising approach for modelling
Externí odkaz:
https://doaj.org/article/deafcaa620d546eaae95fa9134fb4fd7