Zobrazeno 1 - 10
of 187
pro vyhledávání: '"Persello, Claudio"'
Polygonal building outlines are crucial for geographic and cartographic applications. The existing approaches for outline extraction from aerial or satellite imagery are typically decomposed into subtasks, e.g., building masking and vectorization, or
Externí odkaz:
http://arxiv.org/abs/2407.14920
Polygonal building outline extraction has been a research focus in recent years. Most existing methods have addressed this challenging task by decomposing it into several subtasks and employing carefully designed architectures. Despite their accuracy
Externí odkaz:
http://arxiv.org/abs/2407.14912
Autor:
Ghamisi, Pedram, Yu, Weikang, Marinoni, Andrea, Gevaert, Caroline M., Persello, Claudio, Selvakumaran, Sivasakthy, Girotto, Manuela, Horton, Benjamin P., Rufin, Philippe, Hostert, Patrick, Pacifici, Fabio, Atkinson, Peter M.
The convergence of artificial intelligence (AI) and Earth observation (EO) technologies has brought geoscience and remote sensing into an era of unparalleled capabilities. AI's transformative impact on data analysis, particularly derived from EO plat
Externí odkaz:
http://arxiv.org/abs/2405.20868
Accurate global glacier mapping is critical for understanding climate change impacts. Despite its importance, automated glacier mapping at a global scale remains largely unexplored. Here we address this gap and propose Glacier-VisionTransformer-U-Net
Externí odkaz:
http://arxiv.org/abs/2401.15113
Image segmentation aims to partition an image according to the objects in the scene and is a fundamental step in analysing very high spatial-resolution (VHR) remote sensing imagery. Current methods struggle to effectively consider land objects with d
Externí odkaz:
http://arxiv.org/abs/2305.19787
Publikováno v:
In International Journal of Applied Earth Observation and Geoinformation August 2024 132
Clouds and snow have similar spectral features in the visible and near-infrared (VNIR) range and are thus difficult to distinguish from each other in high resolution VNIR images. We address this issue by introducing a shortwave-infrared (SWIR) band w
Externí odkaz:
http://arxiv.org/abs/2201.02350
Autor:
Persello, Claudio, Wegner, Jan Dirk, Hänsch, Ronny, Tuia, Devis, Ghamisi, Pedram, Koeva, Mila, Camps-Valls, Gustau
The synergistic combination of deep learning models and Earth observation promises significant advances to support the sustainable development goals (SDGs). New developments and a plethora of applications are already changing the way humanity will fa
Externí odkaz:
http://arxiv.org/abs/2112.11367
Publikováno v:
In ISPRS Journal of Photogrammetry and Remote Sensing December 2024 218 Part A:405-421
Publikováno v:
In ISPRS Journal of Photogrammetry and Remote Sensing November 2024 217:91-100