SWCGAN: Generative Adversarial Network Combining Swin Transformer and CNN for Remote Sensing Image Super-Resolution

Easy and efficient acquisition of high-resolution remote sensing images is of importance in geographic information systems. Previously, deep neural networks composed of convolutional layers have achieved impressive progress in super-resolution reconstruction. However, the inherent problems of the co...

Полное описание

Библиографические подробности

Главные авторы:	Jingzhi Tu, Gang Mei, Zhengjing Ma, Francesco Piccialli
Формат:	Artigo
Язык:	Inglês
Опубликовано:	IEEE 2022-01-01
Серии:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Предметы:	Convolutional layers generative adversarial network (GAN) remote sensing images super-resolution reconstruction swin transformer
Online-ссылка:	https://ieeexplore.ieee.org/document/9829280/
Метки:	Добавить метку Нет меток, Требуется 1-ая метка записи!