Cargando…
Deep guided transformer dehazing network
Single image dehazing has received a lot of concern and achieved great success with the help of deep-learning models. Yet, the performance is limited by the local limitation of convolution. To address such a limitation, we design a novel deep learning dehazing model by combining the transformer and...
Autores principales: | Zhang, Shengdong, Zhao, Liping, Hu, Keli, Feng, Sheng, Fan, En, Zhao, Li |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10504386/ https://www.ncbi.nlm.nih.gov/pubmed/37714880 http://dx.doi.org/10.1038/s41598-023-41561-z |
Ejemplares similares
-
A Novel Transformer-Based Attention Network for Image Dehazing
por: Gao, Guanlei, et al.
Publicado: (2022) -
Transformer-based progressive residual network for single image dehazing
por: Yang, Zhe, et al.
Publicado: (2022) -
An Efficient Dehazing Algorithm Based on the Fusion of Transformer and Convolutional Neural Network
por: Xu, Jun, et al.
Publicado: (2022) -
GTMNet: a vision transformer with guided transmission map for single remote sensing image dehazing
por: Li, Haiqin, et al.
Publicado: (2023) -
Physical-model guided self-distillation network for single image dehazing
por: Lan, Yunwei, et al.
Publicado: (2022)