[HTML][HTML] Segmentation of individual trees in urban MLS point clouds using a deep learning framework based on cylindrical convolution network
Automatic and accurate instance segmentation of street trees from point clouds is a
fundamental task in urban green space research. Previous studies have achieved …
fundamental task in urban green space research. Previous studies have achieved …
Recurrent residual dual attention network for airborne laser scanning point cloud semantic segmentation
Kernel point convolution (KPConv) can effectively represent the point features of point cloud
data. However, KPConv-based methods just consider the local information of each point …
data. However, KPConv-based methods just consider the local information of each point …
[HTML][HTML] Automating construction of road digital twin geometry using context and location aware segmentation
Abstract Geometric Digital Twins (GDT) represent a critical advancement in road
management, yet their practical implementation encounters a substantial obstacle due to …
management, yet their practical implementation encounters a substantial obstacle due to …
RailSeg: Learning Local-Global Feature Aggregation with Contextual Information for Railway Point Cloud Semantic Segmentation
Incomplete or outdated inventories of railway infrastructures may disrupt the railway sector's
administration and maintenance of transportation infrastructure, thus posing potential threats …
administration and maintenance of transportation infrastructure, thus posing potential threats …
Road-side individual tree segmentation from urban MLS point clouds using metric learning
P Wang, Y Tang, Z Liao, Y Yan, L Dai, S Liu, T Jiang - Remote Sensing, 2023 - mdpi.com
As one of the most important components of urban space, an outdated inventory of road-side
trees may misguide managers in the assessment and upgrade of urban environments …
trees may misguide managers in the assessment and upgrade of urban environments …
Extracting 3-D structural lines of building from ALS point clouds using graph neural network embedded with corner information
The representation quantifies the geometric shape and topology of a building is a necessary
procedure for many urban planning applications. A sharp line framework is a high-level …
procedure for many urban planning applications. A sharp line framework is a high-level …
Instance recognition of street trees from urban point clouds using a three-stage neural network
As one of the most important components of urban space, the geometric and semantic
properties of road trees are crucial for the assessment and upgrade of urban environments …
properties of road trees are crucial for the assessment and upgrade of urban environments …
Automated semantics and topology representation of residential-building space using floor-plan raster maps
Automatically representing the semantics and topology of indoor building spaces from floor-
plans is necessary for many applications, such as architectural design and indoor …
plans is necessary for many applications, such as architectural design and indoor …
A dual attention KPConv Network combined with attention gates for semantic segmentation of ALS point clouds
J Zhao, H Zhou, F Pan - IEEE Transactions on Geoscience and …, 2024 - ieeexplore.ieee.org
Kernel point convolution (KPConv) defines convolutional weights based on Euclidean
distances between kernel points and input points and has shown good segmentation results …
distances between kernel points and input points and has shown good segmentation results …
Mesh-based DGCNN: semantic segmentation of textured 3-D urban scenes
Textured 3-D mesh is one of the final user products in photogrammetry and remote sensing.
However, research on the semantic segmentation of complex urban scenes represented by …
However, research on the semantic segmentation of complex urban scenes represented by …