Dual-attention-guided multiscale feature aggregation network for remote sensing image change detection

H Ren, M **a, L Weng, K Hu… - IEEE Journal of Selected …, 2024‏ - ieeexplore.ieee.org
Remote sensing image change detection plays an important role in urban planning and
environmental monitoring. However, the existing change detection algorithms have limited …

SLDDNet: Stagewise short and long distance dependency network for remote sensing change detection

Z Fu, J Li, L Ren, Z Chen - IEEE Transactions on Geoscience …, 2023‏ - ieeexplore.ieee.org
With the rapid development of society, the pace of land change continues to accelerate.
Consequently, remote sensing change detection (CD) has become a vital method for …

Deep supervision feature refinement attention network for medical image segmentation

Z Fu, J Li, Z Hua, L Fan - Engineering Applications of Artificial Intelligence, 2023‏ - Elsevier
The improvement of medical technology is closely related to the development of computers.
Deep learning methods have become an important means for medical image processing …

GeoFormer: A geometric representation transformer for change detection

J Zhao, L Jiao, C Wang, X Liu, F Liu… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
Deep representation learning has improved automatic remote sensing change detection
(RSCD) in recent years. Existing methods emphasize primarily convolutional neural …

MIFNet: Multi-scale interaction fusion network for remote sensing image change detection

W **e, W Shao, D Li, Y Li, L Fang - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
Change Detection (CD) is a crucial and challenging task in remote sensing observations.
Despite the remarkable progress driven by deep learning in remote sensing change …

MVAFG: Multi-View Fusion and Advanced Feature Guidance Change Detection Network for Remote Sensing Images

X Zhang, Z Wang, J Li, Z Hua - IEEE Journal of Selected Topics …, 2024‏ - ieeexplore.ieee.org
In recent years, change detection (CD) methods have faced challenges in being applied to
various types of remote sensing datasets and related research fields, particularly in the …

High-Resolution Remote Sensing Image Change Detection Based on Fourier Feature Interaction and Multi-scale Perception

Y Chen, S Feng, C Zhao, N Su, W Li… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
As a significant means of Earth observation, change detection in high-resolution remote
sensing images has received extensive attention. Nevertheless, the variability in imaging …

FDFF-Net: A full-scale difference feature fusion network for change detection in high-resolution remote sensing images

F Gu, P **ao, X Zhang, Z Li… - IEEE Journal of Selected …, 2023‏ - ieeexplore.ieee.org
Deep-learning techniques have made significant advances in remote sensing change
detection task. However, it remains a great challenge to detect the details of changed areas …

Segment anything model guided semantic knowledge learning for remote sensing change detection

Z Sun, H Song, K Zhang, G Dong… - ICASSP 2024-2024 …, 2024‏ - ieeexplore.ieee.org
Existing deep learning based remote sensing change detection (RSCD) methods only rely
on binary ground-truth to guide the network learning while neglecting the useful semantic …

LRDE-Net: Large receptive field and image difference enhancement network for remote sensing images change detection

L Li, L Wang, A Du, Y Li - IEEE Journal of Selected Topics in …, 2023‏ - ieeexplore.ieee.org
In the field of remote sensing, change detection is a crucial study area. Deep learning has
made significant strides in the study of remote sensing image change detection during the …