Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: UAV LiDAR Point Cloud Segmentation of A Stack Interchange with Deep
  Neural Networks   Stack interchanges are essential components of transportation systems. Mobile
laser scanning (MLS) systems have been widely used in road infrastructure
mapping, but accurate mapping of complicated multi-layer stack interchanges are
still challenging. This study examined the point clouds collected by a new
Unmanned Aerial Vehicle (UAV) Light Detection and Ranging (LiDAR) system to
perform the semantic segmentation task of a stack interchange. An end-to-end
supervised 3D deep learning framework was proposed to classify the point
clouds. The proposed method has proven to capture 3D features in complicated
interchange scenarios with stacked convolution and the result achieved over 93%
classification accuracy. In addition, the new low-cost semi-solid-state LiDAR
sensor Livox Mid-40 featuring a incommensurable rosette scanning pattern has
demonstrated its potential in high-definition urban mapping.

16
The categories of this paper are: stat
6
The categories of this paper are: astro-ph
5
The categories of this paper are: gr-qc
30
The categories of this paper are: q-alg
7
The categories of this paper are: hep-th
31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
35
The categories of this paper are: mtrl-th
20
The categories of this paper are: acc-phys
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an
34
The categories of this paper are: chem-ph
9
The categories of this paper are: nlin
18
The categories of this paper are: econ
4
The categories of this paper are: cond-mat