Cargando…
Change Detection of Remote Sensing Images Based on Attention Mechanism
In recent years, image processing methods based on convolutional neural networks (CNNs) have achieved very good results. At the same time, many branch techniques have been proposed to improve accuracy. Aiming at the change detection task of remote sensing images, we propose a new network based on U-...
Autores principales: | Chen, Long, Zhang, Dezheng, Li, Peng, Lv, Peng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7468617/ https://www.ncbi.nlm.nih.gov/pubmed/32908477 http://dx.doi.org/10.1155/2020/6430627 |
Ejemplares similares
-
Multiscale Road Extraction in Remote Sensing Images
por: Wulamu, Aziguli, et al.
Publicado: (2019) -
Ship Detection for Optical Remote Sensing Images Based on Visual Attention Enhanced Network
por: Bi, Fukun, et al.
Publicado: (2019) -
HARNU-Net: Hierarchical Attention Residual Nested U-Net for Change Detection in Remote Sensing Images
por: Li, Haojin, et al.
Publicado: (2022) -
MAFF-Net: Multi-Attention Guided Feature Fusion Network for Change Detection in Remote Sensing Images
por: Ma, Jinming, et al.
Publicado: (2022) -
Multiple Attention Mechanism Enhanced YOLOX for Remote Sensing Object Detection
por: Shen, Chao, et al.
Publicado: (2023)