Deep-TEMNet: A Hybrid U-Net–2D LSTM Network for Efficient and Accurate 2.5D Transient Electromagnetic Forward Modeling

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Bibliographische Detailangaben
Veröffentlicht in:	Remote Sensing vol. 17, no. 2 (2025), p. 264
1. Verfasser:	Qu, Zhijie
Weitere Verfasser:	Gao, Yuan, Kang, Xing, Zhang, Xiaojuan
Veröffentlicht:	MDPI AG
Schlagworte:	Finite element method Environmental monitoring Geophysical exploration Accuracy Geological mapping Data processing Deep learning Datasets Modelling Magnetic fields Finite difference time domain method Electromagnetic fields Remote sensing Spatial discrimination Computer applications Modules Electrical resistivity Long short-term memory Python Adaptability Efficiency Geology Machine learning Simulation Exploration Artificial intelligence Fourier transforms Spatial memory Spatial resolution Neural networks High resolution Methods Finite element analysis Information processing Algorithms Real time Subsurface mapping Software
Online-Zugang:	Citation/Abstract Full Text + Graphics Full Text - PDF
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