Zobrazeno 1 - 10
of 1 569
pro vyhledávání: '"G. Vosselman"'
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-1-W1-2023, Pp 439-445 (2023)
The ability of robots to autonomously navigate through 3D environments depends on their comprehension of spatial concepts, ranging from low-level geometry to high-level semantics, such as objects, places, and buildings. To enable such comprehension,
Externí odkaz:
https://doaj.org/article/e5980529c6454ef0b7532150ffa81ced
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-1-W1-2023, Pp 1105-1112 (2023)
Geometric errors in LoD2 building models can be caused by the modeling algorithm but are often related to the quality of input data. One approach to tackling the modeling errors caused by the quality of input data is to collect additional data with a
Externí odkaz:
https://doaj.org/article/a1ac08f10c4b40349c4ea4f4e8d37164
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-2-2022, Pp 275-282 (2022)
The performance of deep learning models in semantic segmentation is dependent on the availability of a large amount of labeled data. However, the influence of label noise, in the form of incorrect annotations, on the performance is significant and mo
Externí odkaz:
https://doaj.org/article/324bcebf8a3e405e990de72d4b7756d7
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B3-2022, Pp 1189-1196 (2022)
Deep detection networks trained with a large amount of annotated data achieve high accuracy in detecting various objects, such as pedestrians, cars, lanes, etc. These models have been deployed and used in many scenarios. A disaster victim detector is
Externí odkaz:
https://doaj.org/article/0a20efa5ee2c45c692fc016a9bbb515d
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-2-2021, Pp 75-82 (2021)
Semantic segmentation for aerial platforms has been one of the fundamental scene understanding task for the earth observation. Most of the semantic segmentation research focused on scenes captured in nadir view, in which objects have relatively small
Externí odkaz:
https://doaj.org/article/e47f46ebcb3b480ab6ce3c43daae477c
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B2-2021, Pp 427-432 (2021)
Semantic segmentation models are often affected by illumination changes, and fail to predict correct labels. Although there has been a lot of research on indoor semantic segmentation, it has not been studied in low-light environments. In this paper w
Externí odkaz:
https://doaj.org/article/5d646d98de254154b8a749d4e55b30cc
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-2-2020, Pp 573-582 (2020)
Degradation and damage detection provides essential information to maintenance workers in routine monitoring and to first responders in post-disaster scenarios. Despite advance in Earth Observation (EO), image analysis and deep learning techniques, t
Externí odkaz:
https://doaj.org/article/867ee3bd9bcd4baaa58691aada560be6
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-1-2020, Pp 223-230 (2020)
In recent years, the importance of indoor mapping increased in a wide range of applications, such as facility management and mapping hazardous sites. The essential technique behind indoor mapping is simultaneous localization and mapping (SLAM) becaus
Externí odkaz:
https://doaj.org/article/ed466f7adf864627856cd6d300733d8f
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-2-2020, Pp 243-250 (2020)
With the development of LiDAR and photogrammetric techniques, more and more point clouds are available with high density and in large areas. Point cloud interpretation is an important step before many real applications like 3D city modelling. Many su
Externí odkaz:
https://doaj.org/article/2022738550204a4f958b9378302fa2f8
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-2-2020, Pp 203-210 (2020)
Knowledge of tree species mapping and of dead wood in particular is fundamental to managing our forests. Although individual tree-based approaches using lidar can successfully distinguish between deciduous and coniferous trees, the classification of
Externí odkaz:
https://doaj.org/article/f78f07959b4a4155959b8d34f6f9ff0a