Related references
Note: Only part of the references are listed.Enhanced Supervised Descent Learning Technique for Electromagnetic Inverse Scattering Problems by the Deep Convolutional Neural Networks
He Ming Yao et al.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION (2022)
Joint Inversion of Audio-Magnetotelluric and Seismic Travel Time Data With Deep Learning Constraint
Rui Guo et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2021)
Enhanced Deep Learning Approach Based on the Deep Convolutional Encoder-Decoder Architecture for Electromagnetic Inverse Scattering Problems
He Ming Yao et al.
IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS (2020)
Physics-Informed Deep Neural Networks for Transient Electromagnetic Analysis
Oameed Noakoasteen et al.
IEEE OPEN JOURNAL OF ANTENNAS AND PROPAGATION (2020)
Enhanced PML Based on the Long Short Term Memory Network for the FDTD Method
He Ming Yao et al.
IEEE ACCESS (2020)
Two-Step Enhanced Deep Learning Approach for Electromagnetic Inverse Scattering Problems
He Ming Yao et al.
IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS (2019)
Machine-Learning-Based PML for the FDTD Method
He Ming Yao et al.
IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS (2019)
Study on a Recurrent Convolutional Neural Network Based FDTD Method
Liangshuai Guo et al.
2019 INTERNATIONAL APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY SYMPOSIUM - CHINA (ACES), VOL 1 (2019)