Change detection from very-high-spatial-resolution optical remote sensing images: Methods, applications, and future directions
Change detection is a vibrant area of research in remote sensing. Thanks to increases in the
spatial resolution of remote sensing images, subtle changes at a finer geometrical scale can …
spatial resolution of remote sensing images, subtle changes at a finer geometrical scale can …
Beyond supervised learning in remote sensing: A systematic review of deep learning approaches
An increasing availability of remote sensing data in the era of geo big-data makes producing
well-represented, reliable training data to be more challenging and requires an excessive …
well-represented, reliable training data to be more challenging and requires an excessive …
Fully convolutional change detection framework with generative adversarial network for unsupervised, weakly supervised and regional supervised change detection
Deep learning for change detection is one of the current hot topics in the field of remote
sensing. However, most end-to-end networks are proposed for supervised change …
sensing. However, most end-to-end networks are proposed for supervised change …
An unsupervised remote sensing change detection method based on multiscale graph convolutional network and metric learning
As a fundamental application, change detection (CD) is widespread in the remote sensing
(RS) community. With the increase in the spatial resolution of RS images, high-resolution …
(RS) community. With the increase in the spatial resolution of RS images, high-resolution …
Unsupervised change detection by cross-resolution difference learning
X Zheng, X Chen, X Lu, B Sun - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Change detection (CD) aims to identify the differences between multitemporal images
acquired over the same geographical area at different times. With the advantages of …
acquired over the same geographical area at different times. With the advantages of …
Deep multiscale Siamese network with parallel convolutional structure and self-attention for change detection
With the wide application of deep learning (DL), change detection (CD) for remote-sensing
images (RSIs) has realized the leap from the traditional to the intelligent methods. However …
images (RSIs) has realized the leap from the traditional to the intelligent methods. However …
UCDFormer: Unsupervised change detection using a transformer-driven image translation
Change detection (CD) by comparing two bitemporal images is a crucial task in remote
sensing. With the advantages of requiring no cumbersome labeled change information …
sensing. With the advantages of requiring no cumbersome labeled change information …
Change detection from synthetic aperture radar images via graph-based knowledge supplement network
Synthetic aperture radar (SAR) image change detection is a vital yet challenging task in the
field of remote sensing image analysis. Most previous works adopt a self-supervised method …
field of remote sensing image analysis. Most previous works adopt a self-supervised method …
[HTML][HTML] A novel unsupervised binary change detection method for VHR optical remote sensing imagery over urban areas
H Fang, P Du, X Wang - International Journal of Applied Earth Observation …, 2022 - Elsevier
Change detection (CD) is a hot topic and has been applied in many fields. Very high
resolution (VHR) images contain the rich spatial information, and are widely used in CD …
resolution (VHR) images contain the rich spatial information, and are widely used in CD …
Brain-inspired remote sensing interpretation: A comprehensive survey
Brain-inspired algorithms have become a new trend in next-generation artificial intelligence.
Through research on brain science, the intelligence of remote sensing algorithms can be …
Through research on brain science, the intelligence of remote sensing algorithms can be …