Self-attention negative feedback network for real-time image super-resolution
In the field of real-time image enhancement, image super-resolution (SR) is an important research hotspot. As an image super-resolution method, deep learning can extract more stable and higher level features. However, image super-resolution processing is an ill posed problem. Due to the lack of self...
Egile Nagusiak: | Xiangbin Liu, Shuqi Chen, Liping Song, Marcin Woźniak, Shuai Liu |
---|---|
Formatua: | Artikulua |
Hizkuntza: | English |
Argitaratua: |
Elsevier
2022-09-01
|
Saila: | Journal of King Saud University: Computer and Information Sciences |
Gaiak: | |
Sarrera elektronikoa: | http://www.sciencedirect.com/science/article/pii/S1319157821001816 |
Antzeko izenburuak
-
SINGLE FRAME SUPER RESOLUTION OF NONCOOPERATIVE IRIS IMAGES
nork: Anand Deshpande, et al.
Argitaratua: (2016-11-01) -
Feature Extraction of 3T3 Fibroblast Microtubule Based on Discrete Wavelet Transform and Lucy–Richardson Deconvolution Methods
nork: Haoxin Bai, et al.
Argitaratua: (2022-05-01) -
Edge-Enhanced with Feedback Attention Network for Image Super-Resolution
nork: Chunmei Fu, et al.
Argitaratua: (2021-03-01) -
A New Approach of Image Denoising Based on Adaptive Multi-Resolution Technique
nork: Lalit Mohan Satapathy, et al.
Argitaratua: (2022-04-01) -
Generating Super Spatial Resolution Products from Sentinel-2 Satellite Images
nork: Mohammad Reza Zargar, et al.
Argitaratua: (2024-03-01)