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 …
EarthNets: Empowering artificial intelligence for Earth observation
Earth observation (EO), aiming at monitoring the state of planet Earth using remote sensing
data, is critical for improving our daily lives and living environment. With a growing number …
data, is critical for improving our daily lives and living environment. With a growing number …
A new learning paradigm for foundation model-based remote-sensing change detection
Change detection (CD) is a critical task to observe and analyze dynamic processes of land
cover. Although numerous deep-learning (DL)-based CD models have performed …
cover. Although numerous deep-learning (DL)-based CD models have performed …
DAM-Net: Flood detection from SAR imagery using differential attention metric-based vision transformers
Flood detection from synthetic aperture radar (SAR) imagery plays an important role in crisis
and disaster management. Based on pre-and post-flood SAR images, flooded areas can be …
and disaster management. Based on pre-and post-flood SAR images, flooded areas can be …
HiCD: Change detection in quality-varied images via hierarchical correlation distillation
Advanced change detection (CD) techniques primarily target image pairs of equal and high
quality. However, variations in imaging conditions and platforms frequently lead to image …
quality. However, variations in imaging conditions and platforms frequently lead to image …
SyntheWorld: A Large-Scale Synthetic Dataset for Land Cover Mapping and Building Change Detection
Synthetic datasets, recognized for their cost effectiveness, play a pivotal role in advancing
computer vision tasks and techniques. However, when it comes to remote sensing image …
computer vision tasks and techniques. However, when it comes to remote sensing image …
[HTML][HTML] High-precision flood detection and mapping via multi-temporal SAR change analysis with semantic token-based transformer
Flood detection in crisis and disaster management is significantly facilitated by the analysis
of synthetic aperture radar (SAR) imagery. Traditional flood detection techniques focus more …
of synthetic aperture radar (SAR) imagery. Traditional flood detection techniques focus more …
RSBuilding: Towards General Remote Sensing Image Building Extraction and Change Detection with Foundation Model
The intelligent interpretation of buildings plays a significant role in urban planning and
management, macroeconomic analysis, population dynamics, etc. Remote sensing image …
management, macroeconomic analysis, population dynamics, etc. Remote sensing image …
Dam-net: Global flood detection from sar imagery using differential attention metric-based vision transformers
The detection of flooded areas using high-resolution synthetic aperture radar (SAR) imagery
is a critical task with applications in crisis and disaster management, as well as …
is a critical task with applications in crisis and disaster management, as well as …
MS-Former: Memory-Supported Transformer for Weakly Supervised Change Detection with Patch-Level Annotations
Fully supervised change detection (CD) methods have achieved significant advancements
in performance, yet they depend severely on acquiring costly pixel-level labels. Considering …
in performance, yet they depend severely on acquiring costly pixel-level labels. Considering …