A Mesh-Free 3-D Deep Learning Electromagnetic Inversion Method Based on Point Clouds
Author:
Affiliation:
1. School of Electronics, Peking University, Beijing, China
2. State Key Laboratory of Millimeter Waves, Southeast University, Nanjing, China
3. ElectroScience Laboratory, The Ohio State University, Columbus, OH, USA
Funder
National Key Research and Development Program of China
Overseas Expertise Introduction Project for Discipline Innovation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Condensed Matter Physics,Radiation
Link
http://xplorestaging.ieee.org/ielx7/22/10213343/10058707.pdf?arnumber=10058707
Reference45 articles.
1. A REVIEW OF DEEP LEARNING APPROACHES FOR INVERSE SCATTERING PROBLEMS (INVITED REVIEW)
2. Integrated Imaging and Inversion of Multi-Physics Data for Exploration Geopysics Applications
3. Learned Global Optimization for Inverse Scattering Problems: Matching Global Search With Computational Efficiency
4. Applications of the BCGS-FFT method to 3-D induction well logging problems
5. Artificial Intelligence: New Frontiers in Real-Time Inverse Scattering and Electromagnetic Imaging
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