Change detection on remote sensing images using dual-branch multilevel intertemporal network
Change detection (CD) of remote sensing (RS) images is mushrooming up accompanied by
the on-going innovation of convolutional neural networks (CNNs). Yet with the high-speed …
the on-going innovation of convolutional neural networks (CNNs). Yet with the high-speed …
Asymmetric cross-attention hierarchical network based on CNN and transformer for bitemporal remote sensing images change detection
X Zhang, S Cheng, L Wang, H Li - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
As an important task in the field of remote sensing (RS) image processing, RS image
change detection (CD) has made significant advances through the use of convolutional …
change detection (CD) has made significant advances through the use of convolutional …
Ultralightweight spatial–spectral feature cooperation network for change detection in remote sensing images
Deep convolutional neural networks (CNNs) have achieved much success in remote
sensing image change detection (CD) but still suffer from two main problems. First, the …
sensing image change detection (CD) but still suffer from two main problems. First, the …
AERNet: An attention-guided edge refinement network and a dataset for remote sensing building change detection
Advancements in Earth observation technology enable the detection of surface changes in
intricate urban environments. Building change detection (BCD) plays a crucial role in urban …
intricate urban environments. Building change detection (BCD) plays a crucial role in urban …
A lightweight transformer network for hyperspectral image classification
Transformer is a powerful tool for capturing long-range dependencies and has shown
impressive performance in hyperspectral image (HSI) classification. However, such power …
impressive performance in hyperspectral image (HSI) classification. However, such power …
Hierarchical attention feature fusion-based network for land cover change detection with homogeneous and heterogeneous remote sensing images
Deep learning techniques have become popular in land cover change detection (LCCD)
with remote sensing images (RSIs). However, many existing networks mostly concentrate on …
with remote sensing images (RSIs). However, many existing networks mostly concentrate on …
Wnet: W-shaped hierarchical network for remote sensing image change detection
Change detection (CD) is a hot research topic in the remote-sensing (RS) community. With
the increasing availability of high-resolution (HR) RS images, there is a growing demand for …
the increasing availability of high-resolution (HR) RS images, there is a growing demand for …
Orsi salient object detection via bidimensional attention and full-stage semantic guidance
The application of optical remote sensing images (ORSIs) is prevalent in many fields.
Accordingly, ORSI-oriented salient object detection (SOD) has attracted more attention in …
Accordingly, ORSI-oriented salient object detection (SOD) has attracted more attention in …
ConvTransNet: A CNN–transformer network for change detection with multiscale global–local representations
Change detection (CD) in optical remote sensing images has significantly benefited from the
development of deep convolutional neural networks (CNNs) due to their strong capability of …
development of deep convolutional neural networks (CNNs) due to their strong capability of …
Spatial-temporal based multihead self-attention for remote sensing image change detection
The neural network-based remote sensing image change detection method faces a large
amount of imaging interference and severe class imbalance problems under high-resolution …
amount of imaging interference and severe class imbalance problems under high-resolution …