Airborne light detection and ranging (LiDAR) has now become industry standard tool for
collecting accurate and dense topographic data at very high speed. These data have found …

This article presents a deep residual network-based fusion framework for hyperspectral and
LiDAR data. In this framework, three new fusion methods are proposed, which are the …

A new framework is proposed for the fusion of hyperspectral and light detection and ranging
(LiDAR) data based on the extinction profiles (EPs), local binary pattern (LBP), and kernel …

A new method of superpixel segmentation-based local pixel neighborhood preserving
embedding (SSLPNPE) is proposed for the fusion of hyperspectral and light detection and …

For semantic classification of LiDAR point clouds, the features derived from the local
geometric descriptors are routinely used as features in (supervised) learning algorithms. In …

To solve the problem of difficult classification of air baggage, we use LMS511 LiDAR to
collect the distance data from the baggage surface to the light-center of LiDAR, propose a …

Both geometric and semantic information are required for a complete understanding of
regions acquired as three-dimensional (3D) point clouds using the Light Detection and …

(57) ABSTRACT A system including one or more computers and one or more storage
devices storing instructions that, when executed by the one or more computers, cause the …

LiDAR point clouds provide rich geometric information, which is particularly useful for the
analysis of complex scenes of urban regions. Finding structural and semantic differences …