Cargando…
Efficient Stereo Depth Estimation for Pseudo-LiDAR: A Self-Supervised Approach Based on Multi-Input ResNet Encoder
Perception and localization are essential for autonomous delivery vehicles, mostly estimated from 3D LiDAR sensors due to their precise distance measurement capability. This paper presents a strategy to obtain a real-time pseudo point cloud from image sensors (cameras) instead of laser-based sensors...
Autores principales: | Hossain, Sabir, Lin, Xianke |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9920229/ https://www.ncbi.nlm.nih.gov/pubmed/36772689 http://dx.doi.org/10.3390/s23031650 |
Ejemplares similares
-
A Novel LiDAR Data Classification Algorithm Combined CapsNet with ResNet
por: Wang, Aili, et al.
Publicado: (2020) -
Vehicle Detection and Tracking with Roadside LiDAR Using Improved ResNet18 and the Hungarian Algorithm
por: Lin, Ciyun, et al.
Publicado: (2023) -
Real-time depth completion based on LiDAR-stereo for autonomous driving
por: Wei, Ming, et al.
Publicado: (2023) -
S-ResNet: An improved ResNet neural model capable of the identification of small insects
por: Wang, Pei, et al.
Publicado: (2022) -
Library-Based Raman
Spectral Identification Using
Multi-Input Hybrid ResNet
por: Chen, Tiejun, et al.
Publicado: (2023)