Oct 24, 2020 · In this paper, we propose a new multi-level feature extraction module to construct a deeper network and obtain more abundant feature maps for SR ...

The method constructs an improved multi-level feature extraction module using the dense connection to obtain a deeper network and richer hierarchical feature ...

An image super-resolution deep learning network based on multi-level feature extraction module. Language: English; Authors: Yang, Xin1 (AUTHOR) yangxin@nuaa ...

Oct 24, 2020 · The method constructs an improved multi-level feature extraction module using the dense connection to obtain a deeper network and richer ...

Jul 1, 2024 · In this paper, we propose improved image super-resolution reconstruction via multi-level information compensation and U-Net network.

An image super-resolution deep learning network based on multi-level feature extraction module. https://doi.org/10.1007/s11042-020-09958-4 ·.

This paper proposes an image super-resolution algorithm based on GAN. We modify the residual block of the original SRGAN generator network into three modules.

This study proposes a multi-level feature interactive image super-resolution network, which is constructed by the convolutional units inspired by nonlinear ...

May 14, 2024 · We propose an efficient Multi-Level Feature Fusion Network for Lightweight Stereo Image Super-Resolution (MFFSSR).

Many advanced deep convolutional neural network (DCNN) methods have proven their efficacy in reconstructing the texture of super-resolution images (SR) from low�...