Registration of large-scale terrestrial laser scanner point clouds: A review and benchmark
This study had two main aims:(1) to provide a comprehensive review of terrestrial laser
scanner (TLS) point cloud registration methods and a better understanding of their strengths …
scanner (TLS) point cloud registration methods and a better understanding of their strengths …
Toward building and civil infrastructure reconstruction from point clouds: A review on data and key techniques
Nowadays, point clouds acquired through laser scanning and stereo matching have
deemed to be one of the best sources for mapping urban scenes. Spatial coordinates of 3-D …
deemed to be one of the best sources for mapping urban scenes. Spatial coordinates of 3-D …
Unsupervised K-means clustering algorithm
KP Sinaga, MS Yang - IEEE access, 2020 - ieeexplore.ieee.org
The k-means algorithm is generally the most known and used clustering method. There are
various extensions of k-means to be proposed in the literature. Although it is an …
various extensions of k-means to be proposed in the literature. Although it is an …
AF2GNN: Graph convolution with adaptive filters and aggregator fusion for hyperspectral image classification
Hyperspectral image classification (HSIC) is essential in remote sensing image analysis.
Applying a graph neural network (GNN) to hyperspectral image (HSI) classification has …
Applying a graph neural network (GNN) to hyperspectral image (HSI) classification has …
Tomato leaf disease identification by restructured deep residual dense network
C Zhou, S Zhou, J Xing, J Song - IEEE Access, 2021 - ieeexplore.ieee.org
As COVID-19 spread worldwide, many major grain-producing countries have adopted
measures to restrict their grain exports; food security has aroused great concern from …
measures to restrict their grain exports; food security has aroused great concern from …
Evaluation of the ICP algorithm in 3D point cloud registration
The iterative closest point (ICP) algorithm is widely used in three-dimensional (3D) point
cloud registration, and it is very stable and robust. However, its biggest drawback is being …
cloud registration, and it is very stable and robust. However, its biggest drawback is being …
A feature-reduction multi-view k-means clustering algorithm
MS Yang, KP Sinaga - IEEE Access, 2019 - ieeexplore.ieee.org
The k-means clustering algorithm is the oldest and most known method in cluster analysis. It
has been widely studied with various extensions and applied in a variety of substantive …
has been widely studied with various extensions and applied in a variety of substantive …
Rapid prediction of urban flood based on disaster-breeding environment clustering and Bayesian optimized deep learning model in the coastal city
H Wang, S Xu, H Xu, Z Wu, T Wang, C Ma - Sustainable Cities and Society, 2023 - Elsevier
Rapid prediction of urban flood is essential for sustainable city and society development.
The data-driven deep learning model is commonly adopted for flood prediction, but it rarely …
The data-driven deep learning model is commonly adopted for flood prediction, but it rarely …
Multi-view point cloud registration based on evolutionary multitasking with bi-channel knowledge sharing mechanism
Multi-view point cloud registration is fundamental in 3D reconstruction. Since there are close
connections between point clouds captured from different viewpoints, registration …
connections between point clouds captured from different viewpoints, registration …
Graph convolutional subspace clustering: A robust subspace clustering framework for hyperspectral image
Hyperspectral image (HSI) clustering is a challenging task due to the high complexity of HSI
data. Subspace clustering has been proven to be powerful for exploiting the intrinsic …
data. Subspace clustering has been proven to be powerful for exploiting the intrinsic …