A review of deep-learning methods for change detection in multispectral remote sensing images
EJ Parelius - Remote Sensing, 2023 - mdpi.com
Remote sensing is a tool of interest for a large variety of applications. It is becoming
increasingly more useful with the growing amount of available remote sensing data …
increasingly more useful with the growing amount of available remote sensing data …
Siamese neural networks in recommendation
N Serrano, A Bellogín - Neural Computing and Applications, 2023 - Springer
Recommender systems are widely adopted as an increasing research and development
area, since they provide users with diverse and useful information tailored to their needs …
area, since they provide users with diverse and useful information tailored to their needs …
Cross-modality attentive feature fusion for object detection in multispectral remote sensing imagery
Cross-modality fusing complementary information of multispectral remote sensing image
pairs can improve the perception ability of detection algorithms, making them more robust …
pairs can improve the perception ability of detection algorithms, making them more robust …
EGDE-Net: A building change detection method for high-resolution remote sensing imagery based on edge guidance and differential enhancement
Buildings are some of the basic spatial elements of a city. Changes in the spatial
distributions of buildings are of great significance for urban planning and monitoring illegal …
distributions of buildings are of great significance for urban planning and monitoring illegal …
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 …
[HTML][HTML] Double U-Net (W-Net): A change detection network with two heads for remote sensing imagery
X Wang, X Yan, K Tan, C Pan, J Ding, Z Liu… - International Journal of …, 2023 - Elsevier
Recently, the deep learning algorithms have been increasingly utilized in remote sensing
change detection. However, incomplete buildings and the blurred edges caused by the …
change detection. However, incomplete buildings and the blurred edges caused by the …
[HTML][HTML] A high-resolution feature difference attention network for the application of building change detection
X Wang, J Du, K Tan, J Ding, Z Liu, C Pan… - International Journal of …, 2022 - Elsevier
Deep learning based change detection has brought a significant improvement in the
accuracy and efficiency when compared with conventional machine learning methods …
accuracy and efficiency when compared with conventional machine learning methods …
An end-to-end supervised domain adaptation framework for cross-domain change detection
Change detection is a crucial but extremely challenging task in remote sensing image
analysis, and much progress has been made with the rapid development of deep learning …
analysis, and much progress has been made with the rapid development of deep learning …
BCE-Net: Reliable building footprints change extraction based on historical map and up-to-date images using contrastive learning
Automatic and periodic recompiling of building databases with up-to-date high-resolution
images has become a critical requirement for rapidly developing urban environments …
images has become a critical requirement for rapidly developing urban environments …