首页> Scientific reports> Efficient seismic data denoising via multi-scale attention network with depthwise separable and residual dilated convolutions.

Efficient seismic data denoising via multi-scale attention network with depthwise separable and residual dilated convolutions.

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第一作者： Zhenjing,Yao

第一单位： Department of Information and Control Engineering, Institute of Disaster Prevention, Sanhe, 065201, China. yaozhenjing000@126.com.;Hebei Key Laboratory of Seismic Disaster Instrument and Monitoring Technology, Sanhe, 065201, Hebei, China. yaozhenjing000@126.com.;Langfang Key Laboratory of Accurately Controlled Active Seismic Source, Sanhe, 065201, Hebei, China. yaozhenjing000@126.com.

作者： Zhenjing,Yao ^[1] ; Lei,Hao ^[2] ; Lan,Qin ^[2] ; Jiahao,Chen ^[2] ; Wenzhe,Li ^[2]

作者单位： Department of Information and Control Engineering, Institute of Disaster Prevention, Sanhe, 065201, China. yaozhenjing000@126.com.;Hebei Key Laboratory of Seismic Disaster Instrument and Monitoring Technology, Sanhe, 065201, Hebei, China. yaozhenjing000@126.com.;Langfang Key Laboratory of Accurately Controlled Active Seismic Source, Sanhe, 065201, Hebei, China. yaozhenjing000@126.com. ^[1] Department of Information and Control Engineering, Institute of Disaster Prevention, Sanhe, 065201, China.;Hebei Key Laboratory of Seismic Disaster Instrument and Monitoring Technology, Sanhe, 065201, Hebei, China.;Langfang Key Laboratory of Accurately Controlled Active Seismic Source, Sanhe, 065201, Hebei, China. ^[2]

关键词 Deep learning Denoising Depthwise separable convolution Multi-scale attention Residual dilated convolution Seismic data

DOI 10.1038/s41598-025-32591-w

PMID 41407810

发布时间 2026-01-24

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