Autonomous measurement and semantic segmentation of non-cooperative targets with deep convolutional neural networks-Reference-Cited by-同舟云学术

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Autonomous measurement and semantic segmentation of non-cooperative targets with deep convolutional neural networks

Published:2022-01-04 Issue: Volume: Page:
ISSN:1868-5137
Container-title:Journal of Ambient Intelligence and Humanized Computing
language:en
Short-container-title:J Ambient Intell Human Comput

Author:

Du Hang,Hu Haidong,Wang Dayi,Xie Xinru,Xu Shuanfeng,Wei Chunling,He Yingzi,Gao Hao

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Science and Technology on Space Intelligent Control Laboratory

Beijing Major Science and Technology Projects

Civil Space Technology Advanced Research Projects of China

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s12652-021-03553-7.pdf

Reference33 articles.

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2. Flores-Abad A, Ma O, Pham K, Ulrich S (2014) A review of space robotics technologies for on-orbit servicing. Prog Aerosp Sci 68:1–26. https://doi.org/10.1016/j.paerosci.2014.03.002

3. He K, Zhang X, Ren S et al (2016) Deep residual learning for image recognition. In: IEEE conference on computer vision & pattern recognition. IEEE Computer Society, pp 770–778

4. Inaba N, Oda M, Asano M (2006) Rescuing a stranded satellite in space—experimental robotic capture of non-cooperative satellites. Trans Jpn Soc Aeronaut Space Sci 48(162):213–220. https://doi.org/10.2322/tjsass.48.213

5. Jigalin A, Gurfil P (2016) Investigation of multiple-baseline stereovision for state estimation of unknown dynamic space targets. Proc Inst Mech Eng Part G J Aerosp Eng 230(2):207–233. https://doi.org/10.1177/0954410015590636

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