Some take into account cloud cover information reported by surface-based observers at meteorological stations – notably cloud fraction, cloud presence at various levels (low, mid, and high clouds), and cloud base height. The principal disadvantage of visual cloud detection is its poor spatial cover...
If height difference between minimum Z value of the cell and other point of cell is less than tolerance point classification is same as cell classification and if not point classification is opposite as cell classification. Five samples of llermanni study area was used to assess the accuracy of...
Study on Calculating Methods of Young Women Body Circumferences Based on 3D Point-Cloud Data In this research, 425 female students were selected as the research objects. Point clouds were obtained by 3D body scanner , then the characteristics of fe... PY Gu,T Chen,L Huang,... - 《Advance...
A unified framework is proposed for classifying the MLS point clouds based on segments. A set of features for each segment are well-designed, which can be used to effectively distinguish nine common object classes in urban street scenes. A publicly available point cloud dataset with ground truth ...
The project is based on pytorch. Point clouds of single trees are augmented and projected to grids (4 side views, 1 top view, 1 bottom view, 1 detail view 1 - 1.5 m height). The dataset is available on Zenodo. The training weights are available on FreiData. Classification is done with...
Standard cloud algorithms rely on multispectral signatures to identify high, medium, and low clouds. In contrast, the present study classifies stratocumulu... RM Welch,SK Sengupta,DW Chen - 《Journal of Geophysical Research》 被引量: 110发表: 1988年 Classifying individual tree genera using stepwis...
Therefore, three subtypes of fair-weather cumulus clouds are identified based on the nature of their interaction with the mixed layer: forced, active and passive clouds. Forced clouds, the visible tracers within the tops of some mixed-layer thermals, are totally embedded within the mixed layer. ...
This paper focuses on detecting and classifying pole-like objects from point clouds obtained in urban areas. To achieve our goal, we propose a system consisting of three stages: localization, segmentation and classification. The localization algorithm based on slicing, clustering, pole seed generation...
2.1 Classification of LiDAR Point Clouds To classify point clouds with traditional classifiers such as random forest, typically geometric features based on the 3D points within a defined neighbourhood are extracted in a first step (Weinmann et al. 2015). These features are later used for the clas...
(s)is the absorption coefficient of water vapor at the distance ofsand pre-calculated for each month based on humidity data obtained from 2015 to 2017. The attenuation in clouds, precipitation and other gases has not yet been calibrated. However, these attenuations are limited because the radar...