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[HTML][HTML] Deep learning-based change detection in remote sensing images: A review
Images gathered from different satellites are vastly available these days due to the fast
development of remote sensing (RS) technology. These images significantly enhance the …
development of remote sensing (RS) technology. These images significantly enhance the …
A review of multi-class change detection for satellite remote sensing imagery
Change Detection (CD) provides a research basis for environmental monitoring, urban
expansion and reconstruction as well as disaster assessment, by identifying the changes of …
expansion and reconstruction as well as disaster assessment, by identifying the changes of …
Changemamba: Remote sensing change detection with spatio-temporal state space model
Convolutional neural networks (CNNs) and Transformers have made impressive progress in
the field of remote sensing change detection (CD). However, both architectures have …
the field of remote sensing change detection (CD). However, both architectures have …
Multiscale diff-changed feature fusion network for hyperspectral image change detection
For hyperspectral image (HSI) change detection (CD), multiscale features are usually used
to construct the detection models. However, the existing studies only consider the multiscale …
to construct the detection models. However, the existing studies only consider the multiscale …
TransUNetCD: A hybrid transformer network for change detection in optical remote-sensing images
Q Li, R Zhong, X Du, Y Du - IEEE Transactions on Geoscience …, 2022 - ieeexplore.ieee.org
In the change detection (CD) task, the UNet architecture has achieved superior results.
However, due to the inherent limitation of convolution operations, UNet is inadequate in …
However, due to the inherent limitation of convolution operations, UNet is inadequate in …
[HTML][HTML] A spatial-temporal attention-based method and a new dataset for remote sensing image change detection
Remote sensing image change detection (CD) is done to identify desired significant
changes between bitemporal images. Given two co-registered images taken at different …
changes between bitemporal images. Given two co-registered images taken at different …
DASNet: Dual attentive fully convolutional Siamese networks for change detection in high-resolution satellite images
Change detection is a basic task of remote sensing image processing. The research
objective is to identify the change information of interest and filter out the irrelevant change …
objective is to identify the change information of interest and filter out the irrelevant change …
HANet: A hierarchical attention network for change detection with bitemporal very-high-resolution remote sensing images
Benefiting from the developments in deep learning technology, deep-learning-based
algorithms employing automatic feature extraction have achieved remarkable performance …
algorithms employing automatic feature extraction have achieved remarkable performance …
Optical remote sensing image change detection based on attention mechanism and image difference
X Peng, R Zhong, Z Li, Q Li - IEEE Transactions on Geoscience …, 2020 - ieeexplore.ieee.org
This study presents a new end-to-end change detection network, called difference-
enhancement dense-attention convolutional neural network (DDCNN), that is designed for …
enhancement dense-attention convolutional neural network (DDCNN), that is designed for …
Slow down to go better: A survey on slow feature analysis
Temporal data contain a wealth of valuable information, playing an essential role in various
machine-learning tasks. Slow feature analysis (SFA), one of the most classic temporal …
machine-learning tasks. Slow feature analysis (SFA), one of the most classic temporal …