Cargando…
A Novel Transformer-Based Attention Network for Image Dehazing
Image dehazing is challenging due to the problem of ill-posed parameter estimation. Numerous prior-based and learning-based methods have achieved great success. However, most learning-based methods use the changes and connections between scale and depth in convolutional neural networks for feature e...
Autores principales: | Gao, Guanlei, Cao, Jie, Bao, Chun, Hao, Qun, Ma, Aoqi, Li, Gang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9105677/ https://www.ncbi.nlm.nih.gov/pubmed/35591118 http://dx.doi.org/10.3390/s22093428 |
Ejemplares similares
-
Residual Spatial and Channel Attention Networks for Single Image Dehazing
por: Jiang, Xin, et al.
Publicado: (2021) -
Transformer-based progressive residual network for single image dehazing
por: Yang, Zhe, et al.
Publicado: (2022) -
Multi-Scale Attention Feature Enhancement Network for Single Image Dehazing
por: Dong, Weida, et al.
Publicado: (2023) -
Deep guided transformer dehazing network
por: Zhang, Shengdong, et al.
Publicado: (2023) -
Single image mixed dehazing method based on numerical iterative model and DehazeNet
por: Jiao, Wenjiang, et al.
Publicado: (2021)