[HTML][HTML] Deep learning-based change detection in remote sensing images: A review

A Shafique, G Cao, Z Khan, M Asad, M Aslam - Remote Sensing, 2022‏ - mdpi.com
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 …

A review of multi-class change detection for satellite remote sensing imagery

Q Zhu, X Guo, Z Li, D Li - Geo-spatial Information Science, 2024‏ - Taylor & Francis
Change Detection (CD) provides a research basis for environmental monitoring, urban
expansion and reconstruction as well as disaster assessment, by identifying the changes of …

Changemamba: Remote sensing change detection with spatio-temporal state space model

H Chen, J Song, C Han, J **a… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
Convolutional neural networks (CNNs) and Transformers have made impressive progress in
the field of remote sensing change detection (CD). However, both architectures have …

Multiscale diff-changed feature fusion network for hyperspectral image change detection

F Luo, T Zhou, J Liu, T Guo, X Gong… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
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 …

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 …

[HTML][HTML] A spatial-temporal attention-based method and a new dataset for remote sensing image change detection

H Chen, Z Shi - Remote sensing, 2020‏ - mdpi.com
Remote sensing image change detection (CD) is done to identify desired significant
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

J Chen, Z Yuan, J Peng, L Chen… - IEEE Journal of …, 2020‏ - ieeexplore.ieee.org
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 …

HANet: A hierarchical attention network for change detection with bitemporal very-high-resolution remote sensing images

C Han, C Wu, H Guo, M Hu… - IEEE Journal of Selected …, 2023‏ - ieeexplore.ieee.org
Benefiting from the developments in deep learning technology, deep-learning-based
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 …

Slow down to go better: A survey on slow feature analysis

P Song, C Zhao - IEEE Transactions on Neural Networks and …, 2022‏ - ieeexplore.ieee.org
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 …