Prestack seismic random noise attenuation using the wavelet-inspired invertible network with atrous convolutions spatial pyramid
Convolutional Neural Network (CNN) is widely used in seismic data denoising due to its simplicity and effectiveness. However, traditional seismic denoising methods based on CNN ignore multi-scale features of seismic data in the wavelet domain. The lack of these features will decrease the accuracy of...
Main Authors: | Liangsheng He, Hao Wu, Xiaotao Wen |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2023-02-01
|
Series: | Frontiers in Earth Science |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2023.1090620/full |
Similar Items
-
An Adaptive Atrous Spatial Pyramid Pooling Network for Hyperspectral Classification
by: Tianxing Zhu, et al.
Published: (2023-12-01) -
A high-effective multitask surface defect detection method based on CBAM and atrous convolution
by: Xin XIE, et al.
Published: (2022-11-01) -
Modified UNet++ with atrous spatial pyramid pooling for blood cell image segmentation
by: Kun Lan, et al.
Published: (2023-01-01) -
Mixed-Scale Unet Based on Dense Atrous Pyramid for Monocular Depth Estimation
by: Yifan Yang, et al.
Published: (2021-01-01) -
Constrained Image Splicing Detection and Localization With Attention-Aware Encoder-Decoder and Atrous Convolution
by: Yaqi Liu, et al.
Published: (2020-01-01)