Enhancing the Resolution of Seismic Images With a Network Combining CNN and Transformer.

Perception-oriented generative adversarial network for retinal fundus image super-resolution.

SHBGAN: Hybrid Bilateral Attention GAN for Seismic Image Super-Resolution Reconstruction.

Joint-Guided Denoising Network for Erratic Noise Attenuation.

Computing Angle Gathers From Imaging of Multiples Using a Poynting Vector Method for Improving Angular Illumination.

EFGW-UNet: A Deep-Learning-Based Approach for Weak Signal Recovery in Seismic Data.

Global-Feature-Fusion and Multiscale Network for Low-Frequency Extrapolation.

Seismic Interpolation Transformer for Consecutively Missing Data: A Case Study in DAS-VSP Data.

HGMFN:Hierarchical Guided Multicascade Feedback Network for Complex Seismic Data Reconstruction.

Mutual-guided scale-aggregation denoising network for seismic noise attenuation.

Remote Sensing Image Dehazing through an Unsupervised Generative Adversarial Network.

Unsupervised Low-Light Image Enhancement Based on Generative Adversarial Network.

Multiscale Encoder-Decoder Network for DAS Data Simultaneous Denoising and Reconstruction.

Least-Squares Reverse Time Migration Using the Inverse Scattering Imaging Condition.

RMCHN: A Residual Modular Cascaded Heterogeneous Network for Noise Suppression in DAS-VSP Records.

Multiscale Residual Pyramid Network for Seismic Background Noise Attenuation.

Seismic Random Noise Attenuation by Applying Multiscale Denoising Convolutional Neural Network.

RCEN: A Deep-Learning-Based Background Noise Suppression Method for DAS-VSP Records.

Random and Coherent Noise Suppression in DAS-VSP Data by Using a Supervised Deep Learning Method.

Seismic Random Noise Suppression by Using Adaptive Fractal Conservation Law Method Based on Stationarity Testing.

A Deep-Learning-Based Denoising Method for Multiarea Surface Seismic Data.

New Suppression Technology for Low-Frequency Noise in Desert Region: The Improved Robust Principal Component Analysis Based on Prediction of Neural Network.

Power Quality Disturbance Recognition Based on Multiresolution S-Transform and Decision Tree.

Research on Recognition Method of Electrical Components Based on YOLO V3.