[HTML][HTML] CapViT: Cross-context capsule vision transformers for land cover classification with airborne multispectral LiDAR data

Y Yu, T Jiang, J Gao, H Guan, D Li, S Gao… - International Journal of …, 2022 - Elsevier
Equipped with multiple channels of laser scanners, multispectral light detection and ranging
(MS-LiDAR) devices possess more advanced prospects in earth observation tasks …

[HTML][HTML] Review on active and passive remote sensing techniques for road extraction

J Jia, H Sun, C Jiang, K Karila, M Karjalainen… - Remote Sensing, 2021 - mdpi.com
Digital maps of road networks are a vital part of digital cities and intelligent transportation. In
this paper, we provide a comprehensive review on road extraction based on various remote …

Land-cover classification of multispectral LiDAR data using CNN with optimized hyper-parameters

S Pan, H Guan, Y Chen, Y Yu, WN Gonçalves… - ISPRS Journal of …, 2020 - Elsevier
Abstract Multispectral LiDAR (Light Detection And Ranging) is characterized of the
completeness and consistency of its spectrum and spatial geometric data, which provides a …

[HTML][HTML] Multispectral LiDAR point cloud classification using SE-PointNet++

Z Jing, H Guan, P Zhao, D Li, Y Yu, Y Zang, H Wang… - Remote Sensing, 2021 - mdpi.com
A multispectral light detection and ranging (LiDAR) system, which simultaneously collects
spatial geometric data and multi-wavelength intensity information, opens the door to three …

[HTML][HTML] Deep learning for detecting multi-level driver fatigue using physiological signals: A comprehensive approach

M Peivandi, SZ Ardabili, S Sheykhivand, S Danishvar - Sensors, 2023 - mdpi.com
A large share of traffic accidents is related to driver fatigue. In recent years, many studies
have been organized in order to diagnose and warn drivers. In this research, a new …

[HTML][HTML] Airborne multispectral LiDAR point cloud classification with a feature reasoning-based graph convolution network

P Zhao, H Guan, D Li, Y Yu, H Wang, K Gao… - International Journal of …, 2021 - Elsevier
This paper presents a feature reasoning-based graph convolution network (FR-GCNet) to
improve the classification accuracy of airborne multispectral LiDAR (MS-LiDAR) point …

[HTML][HTML] Building extraction from airborne multi-spectral LiDAR point clouds based on graph geometric moments convolutional neural networks

D Li, X Shen, Y Yu, H Guan, J Li, G Zhang, D Li - Remote Sensing, 2020 - mdpi.com
Building extraction has attracted much attentions for decades as a prerequisite for many
applications and is still a challenging topic in the field of photogrammetry and remote …

A spatial–spectral classification framework for multispectral LiDAR

S Shi, B Chen, S Bi, J Li, W Gong, J Sun… - Geo-Spatial …, 2023 - Taylor & Francis
ABSTRACT Precise classification of Light Detection and Ranging (LiDAR) point cloud is a
fundamental process in various applications, such as land cover mapping, forestry …

3d lidar map compression for efficient localization on resource constrained vehicles

H Yin, Y Wang, L Tang, X Ding… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Large scale 3D maps constructed via LiDAR sensor are widely used on intelligent vehicles
for localization in outdoor scenes. However, loading, communication and processing of the …

[HTML][HTML] Multispectral Light Detection and Ranging Technology and Applications: A Review

N Takhtkeshha, G Mandlburger, F Remondino… - Sensors, 2024 - mdpi.com
Light Detection and Ranging (LiDAR) is a well-established active technology for the direct
acquisition of 3D data. In recent years, the geometric information collected by LiDAR …