Structural residual learning for single image rain removal

To alleviate the adverse effect of rain streaks in image processing tasks, CNN-based single image rain removal methods have been recently proposed. However, the performance of these deep learning methods largely relies on the covering range of rain shapes contained in the pre-collected training rain...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Knowledge-based systems Ročník 213; s. 106595
Hlavní autori:	Wang, Hong, Wu, Yichen, Xie, Qi, Zhao, Qian, Liang, Yong, Zhang, Shijun, Meng, Deyu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 15.02.2021 Elsevier Science Ltd
Predmet:	Computer architecture Deep learning Experiments Generalization Generalization performance Image processing Interpretability Learning Multi-scale convolutional sparse coding Networks Prior knowledge Rain Regularization Side effects Single image deraining Training Deep learning Generalization performance Single image deraining Interpretability Multi-scale convolutional sparse coding
ISSN:	0950-7051, 1872-7409
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!