Spatial-temporal 3D dependency matching with self-supervised deep learning for monocular visual sensing-Reference-Cited by-同舟云学术

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Spatial-temporal 3D dependency matching with self-supervised deep learning for monocular visual sensing

Published:2022-04 Issue: Volume:481 Page:11-21
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Song Chengqun,Niu Maolong,Liu Zhaopeng,Cheng Jun,Wang Peng,Li Hongjian,Hao Luoying

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference60 articles.

1. A hybrid feature model and deep learning based fault diagnosis for unmanned aerial vehicle sensors;Guo;Neurocomputing,2018

2. Input saturated visual servoing for unmanned aerial vehicles;Xie;IEEE-ASME Trans. Mechatron.,2017

3. Trajectory tracking of constrained robotic systems via a hybrid control strategy;Sun;Neurocomputing,2019

4. Towards lifelong assistive robotics: a tight coupling between object perception and manipulation;Kasaei;Neurocomputing,2018

5. Self-localization based on visual lane marking maps: an accurate low-cost approach for autonomous driving;Vivacqua;IEEE Trans. Intell. Transp. Syst.,2018

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