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 …
expansion and reconstruction as well as disaster assessment, by identifying the changes of …
Bi-temporal semantic reasoning for the semantic change detection in HR remote sensing images
Semantic change detection (SCD) extends the multiclass change detection (MCD) task to
provide not only the change locations but also the detailed land-cover/land-use (LCLU) …
provide not only the change locations but also the detailed land-cover/land-use (LCLU) …
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 …
MFVNet: A deep adaptive fusion network with multiple field-of-views for remote sensing image semantic segmentation
In recent years, the remote sensing image (RSI) semantic segmentation attracts increasing
research interest due to its wide application. RSIs are difficult to be processed holistically on …
research interest due to its wide application. RSIs are difficult to be processed holistically on …
RADANet: Road augmented deformable attention network for road extraction from complex high-resolution remote-sensing images
L Dai, G Zhang, R Zhang - IEEE Transactions on Geoscience …, 2023 - ieeexplore.ieee.org
Extracting roads from complex high-resolution remote sensing images to update road
networks has become a recent research focus. How to apply the contextual spatial …
networks has become a recent research focus. How to apply the contextual spatial …
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 …
Novel piecewise distance based on adaptive region key-points extraction for LCCD with VHR remote-sensing images
Land cover change detection (LCCD) with very high-resolution remote-sensing images
(VHR_RSIs) is important in observing surface change on Earth. However, pseudo-changes …
(VHR_RSIs) is important in observing surface change on Earth. However, pseudo-changes …
Advances and challenges in deep learning-based change detection for remote sensing images: A review through various learning paradigms
Change detection (CD) in remote sensing (RS) imagery is a pivotal method for detecting
changes in the Earth's surface, finding wide applications in urban planning, disaster …
changes in the Earth's surface, finding wide applications in urban planning, disaster …
Universal domain adaptation for remote sensing image scene classification
The domain adaptation (DA) approaches available to date are usually not well suited for
practical DA scenarios of remote sensing image classification since these methods (such as …
practical DA scenarios of remote sensing image classification since these methods (such as …
Road extraction from satellite imagery by road context and full-stage feature
Road extraction from satellite imagery is vital in a broad range of applications. However,
extracting complete roads is challenging due to road occlusions caused by the …
extracting complete roads is challenging due to road occlusions caused by the …