Faster R-CNN Learning-Based Semantic Filter for Geometry Estimation and Its Application in vSLAM Systems-Reference-Cited by-同舟云学术

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Faster R-CNN Learning-Based Semantic Filter for Geometry Estimation and Its Application in vSLAM Systems

Published:2021 Issue: Volume: Page:1-10
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Shao Chunyan^ORCID,Zhang Limin,Pan Wang

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/4358928/09339874.pdf?arnumber=9339874

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep Learning-Based Vision Systems for Robot Semantic Navigation: An Experimental Study;Technologies;2024-09-10

2. ULG-SLAM: A Novel Unsupervised Learning and Geometric Feature-Based Visual SLAM Algorithm for Robot Localizability Estimation;Remote Sensing;2024-05-30

3. A Semantic Topology Graph to Detect Re-Localization and Loop Closure of the Visual Simultaneous Localization and Mapping System in a Dynamic Environment;Sensors;2023-10-13

4. A survey on semantic communications: technologies, solutions, applications and challenges;Digital Communications and Networks;2023-06

5. Loop Closure Detection With Bidirectional Manifold Representation Consensus;IEEE Transactions on Intelligent Transportation Systems;2023-04

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