Change detection based on artificial intelligence: State-of-the-art and challenges
Change detection based on remote sensing (RS) data is an important method of detecting
changes on the Earth's surface and has a wide range of applications in urban planning …
changes on the Earth's surface and has a wide range of applications in urban planning …
Analysis on change detection techniques for remote sensing applications: A review
Satellite images taken on the earth's surface are analyzed to identify the spatial and
temporal changes that have occurred naturally or manmade. Real-time prediction of change …
temporal changes that have occurred naturally or manmade. Real-time prediction of change …
A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images
Change detection in high resolution remote sensing images is crucial to the understanding
of land surface changes. As traditional change detection methods are not suitable for the …
of land surface changes. As traditional change detection methods are not suitable for the …
SemiCDNet: A semisupervised convolutional neural network for change detection in high resolution remote-sensing images
Change detection (CD) is one of the main applications of remote sensing. With the
increasing popularity of deep learning, most recent developments of CD methods have …
increasing popularity of deep learning, most recent developments of CD methods have …
CLNet: Cross-layer convolutional neural network for change detection in optical remote sensing imagery
Change detection plays a crucial role in observing earth surface transition and has been
widely investigated using deep learning methods. However, the current deep learning …
widely investigated using deep learning methods. However, the current deep learning …
Fully transformer network for change detection of remote sensing images
Recently, change detection (CD) of remote sensing images have achieved great progress
with the advances of deep learning. However, current methods generally deliver incomplete …
with the advances of deep learning. However, current methods generally deliver incomplete …
Difference enhancement and spatial–spectral nonlocal network for change detection in VHR remote sensing images
The popular Siamese convolutional neural networks (CNNs) for remote sensing (RS) image
change detection (CD) often suffer from two problems. First, they either ignore the original …
change detection (CD) often suffer from two problems. First, they either ignore the original …
Transy-net: Learning fully transformer networks for change detection of remote sensing images
In the remote sensing field, change detection (CD) aims to identify and localize the changed
regions from dual-phase images over the same places. Recently, it has achieved great …
regions from dual-phase images over the same places. Recently, it has achieved great …
Remote sensing image change detection transformer network based on dual-feature mixed attention
X Song, Z Hua, J Li - IEEE Transactions on Geoscience and …, 2022 - ieeexplore.ieee.org
Change detection (CD) of high-resolution remote sensing (RS) images is a basic task in RS
image processing tasks. In recent years, CD tasks have made many attempts in pure …
image processing tasks. In recent years, CD tasks have made many attempts in pure …
A hierarchical self-attention augmented Laplacian pyramid expanding network for change detection in high-resolution remote sensing images
Change detection methods can achieve high learning ability and recognition accuracy with
the introduction of deep convolutional neural networks, but due to the influence of the …
the introduction of deep convolutional neural networks, but due to the influence of the …