Cone-Shaped Space Target Inertia Characteristics Identification by Deep Learning With Compressed Dataset-Reference-Cited by-同舟云学术

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Cone-Shaped Space Target Inertia Characteristics Identification by Deep Learning With Compressed Dataset

Published:2022-07 Issue:7 Volume:70 Page:5217-5226
ISSN:0018-926X
Container-title:IEEE Transactions on Antennas and Propagation
language:
Short-container-title:IEEE Trans. Antennas Propagat.

Author:

Wang Shaoran¹,Li Mengmeng¹^ORCID,Yang Tian¹,Ai Xia²,Liu Jiaqi²,Andriulli Francesco P.³^ORCID,Ding Dazhi¹^ORCID

Affiliation:

1. Department of Communication Engineering, Nanjing University of Science and Technology, Nanjing, China

2. National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics, Beijing, China

3. Politecnico di Torino of Turin, Turin, Italy

Funder

Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/8/9843191/09773027.pdf?arnumber=9773027

Reference41 articles.

1. Deep Residual Learning for Image Recognition

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4. Going deeper with convolutions

5. Deep Learning to Accelerate Scatterer-to-Field Mapping for Inverse Design of Dielectric Metasurfaces

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