SMCNet: State-Space Model for Enhanced Corruption Robustness in 3D Classification
Accurate classification of three-dimensional (3D) point clouds in real-world environments is often impeded by sensor noise, occlusions, and incomplete data. To overcome these challenges, we propose SMCNet, a robust multimodal framework for 3D point cloud classification. SMCNet combines multi-view pr...
Saved in:
| Main Authors: | Junhui Li, Bangju Huang, Lei Pan |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/24/23/7861 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Detection Method for Open–Close States of High-Voltage Disconnector in Smoky Environments
by: Lujia Wang, et al.
Published: (2025-02-01) -
MMTSCNet: Multimodal Tree Species Classification Network for Classification of Multi-Source, Single-Tree LiDAR Point Clouds
by: Jan Richard Vahrenhold, et al.
Published: (2025-04-01) -
An innovative framework for incorporating iPhone LiDAR point cloud in digitized documentation of road operations
by: Srikulnath Nilnoree, et al.
Published: (2025-03-01) -
Efficient tree species classification using machine and deep learning algorithms based on UAV-LiDAR data in North China
by: Hanyu Zhang, et al.
Published: (2025-06-01) -
Standard Classes for Urban Topographic Mapping with ALS: Classification Scheme and a First Implementation
by: Agata Walicka, et al.
Published: (2025-08-01)