GTCN: Gated Temporal Convolutional Networks for Controlled-Source Electromagnetic Data Denoising

To improve the signal-to-noise ratio (SNR) of controlled-source electromagnetic (CSEM) data observed in strong interference environments, a new deep learning network is proposed and named gated temporal convolutional network (GTCN) to map noisy sequences to high-quality sequences. This network is an...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 2024, Vol.62, p.1-14
Hauptverfasser:	Li, Guang, Wu, Shouli, Cai, Hongzhu, Chen, Chaojian, Chen, Hui, Xiao, Donghan, Yan, Jiayong
Format:	Artikel
Sprache:	eng
Schlagworte:	Controlled-source electromagnetic (CSEM) data Convolutional neural networks Deep learning denoising Effectiveness Electromagnetics gated recurrent unit (GRU) Information processing Logic gates Networks Noise measurement Noise reduction Observational learning recurrent neural networks (RNNs) Reliability Sequences Signal to noise ratio Synthetic data temporal convolutional networks (TCNs) Time measurement Time series Training
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