Registration of large-scale terrestrial laser scanner point clouds: A review and benchmark

Z Dong, F Liang, B Yang, Y Xu, Y Zang, J Li… - ISPRS Journal of …, 2020 - Elsevier
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 …

Overcoming the limits of cross-sensitivity: pattern recognition methods for chemiresistive gas sensor array

H Mei, J Peng, T Wang, T Zhou, H Zhao, T Zhang… - Nano-micro letters, 2024 - Springer
As information acquisition terminals for artificial olfaction, chemiresistive gas sensors are
often troubled by their cross-sensitivity, and reducing their cross-response to ambient gases …

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 …

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 …

Graph convolutional subspace clustering: A robust subspace clustering framework for hyperspectral image

Y Cai, Z Zhang, Z Cai, X Liu, X Jiang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
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 …