Pole-Like Objects Segmentation and Multiscale Classification-Based Fusion from Mobile Point Clouds in Road Scenes
Real-time acquisition and intelligent classification of pole-like street-object point clouds are of great significance in the construction of smart cities. Efficient point cloud processing technology in road scenes can accelerate the development of intelligent transportation and promote the developm...
Enregistré dans:
Auteurs principaux: | Ziyang Wang, Lin Yang, Yehua Sheng, Mi Shen |
---|---|
Format: | article |
Langue: | EN |
Publié: |
MDPI AG
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/a01c54f8799d4d0095cfb7e4e43b2012 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
GACM: A Graph Attention Capsule Model for the Registration of TLS Point Clouds in the Urban Scene
par: Jianjun Zou, et autres
Publié: (2021) -
Contrastive Learning for 3D Point Clouds Classification and Shape Completion
par: Danish Nazir, et autres
Publié: (2021) -
Semantic Point Cloud-Based Adaptive Multiple Object Detection and Tracking for Autonomous Vehicles
par: Soyeong Kim, et autres
Publié: (2021) -
CDUNet: Cloud Detection UNet for Remote Sensing Imagery
par: Kai Hu, et autres
Publié: (2021) -
Research on Fast Target Positioning Method of Self-Calibration Manipulator
par: Xuhui Ye, et autres
Publié: (2021)