Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Perpetual Hope Akwensi"'
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 128, Iss , Pp 103730- (2024)
The success of transformer networks in the natural language processing and 2D vision domains has encouraged the adaptation of transformers to 3D computer vision tasks. However, most of the existing approaches employ standard backpropagation (SBP). SB
Externí odkaz:
https://doaj.org/article/47b32aa018b44a6ea6d2cc4ebd114bb1
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 120, Iss , Pp 103302- (2023)
Urban scene-level 3D point cloud labeling is a very laborious and expensive task compared to images. Conversely however, image processing techniques, deep learning or otherwise are more established and mature. Thus, in a multi-source data environment
Externí odkaz:
https://doaj.org/article/caf0f7e84dd344ccae7da829c8b08d0f
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 1055-1067 (2020)
Accurate individual tree segmentation is an important basis for the subsequent calculation and analysis of forestry parameters. However, rasterized canopy height model based methods often suffer from 3-D information loss due to the interpolation oper
Externí odkaz:
https://doaj.org/article/11d5e1d506ef416480a87e0c1410cdda
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 19:1-5
The reconstruction of 3-D models of power pylons from light detection and ranging (LiDAR) data plays an important role in power transmission safety. However, accurate reconstruction of power pylon models still faces challenges, e.g., complex structur
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 18:1466-1470
Airborne light detection and ranging (LiDAR) point clouds have become growingly popular as a reliable data source for 3-D digital building model reconstruction. Therefore, we develop a label-constraint approach for automatically detecting building ro
Autor:
Perpetual Hope Akwensi, Ruisheng Wang
Publikováno v:
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium.
Publikováno v:
ISPRS Journal of Photogrammetry and Remote Sensing. 173:238-261
The increasing availability of both indoor positioning services and sensors for 3D data capture, such as RGB-D sensors, allows the provision of indoor spatial information services for indoor localization-based applications. To efficiently realize the
Publikováno v:
Applied Geomatics. 13:453-465
Remotely sensed image segmentation and classification form a very important part of remote sensing which involves geo-data processing and analysis. Artificial neural networks (ANNs) are powerful machine learning approaches that have been successfully
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 17:504-508
Point cloud feature extraction as a classification task is crucial in maximizing the efficient downstream applicability of raw point clouds. With the goal of learning optimum features for efficient classification of a multi-class point cloud for down
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 1055-1067 (2020)
Accurate individual tree segmentation is an important basis for the subsequent calculation and analysis of forestry parameters. However, rasterized canopy height model based methods often suffer from 3-D information loss due to the interpolation oper