Convolutional neural network-based perturbation shooting and bouncing rays solution for recognition of targets with uncertain geometrical shapes

DOI10.1016/J.ENGANABOUND.2022.07.016OpenAlexW4289260030WikidataQ113875161 ScholiaQ113875161MaRDI QIDQ2085967

Zi He, Da-Zhi Ding, Sheng-Kai Sun, Fan Ding

Publication date: 19 October 2022

Published in: Engineering Analysis with Boundary Elements (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.enganabound.2022.07.016

zbMATH Keywords

ISARconvolutional neural network (CNN)shooting and bouncing rays (SBR)varying geometrical shapes

Mathematics Subject Classification ID

Biology and other natural sciences (92-XX) Computer science (68-XX)

Cites Work

• A Hybrid Quantitative Method for Inverse Scattering of Multiple Dielectric Objects
• Study of resolution and super resolution in electromagnetic imaging for half-space problems
• Efficient Microwave Imaging Algorithm Based on Hybridization of the Linear Sampling and Level Set Methods

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