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 …
Exchange means change: An unsupervised single-temporal change detection framework based on intra-and inter-image patch exchange
Change detection is a critical task in studying the dynamics of ecosystems and human
activities using multi-temporal remote sensing images. While deep learning has shown …
activities using multi-temporal remote sensing images. While deep learning has shown …
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 …
Methods and datasets on semantic segmentation for Unmanned Aerial Vehicle remote sensing images: A review
Abstract Unmanned Aerial Vehicle (UAV) has seen a dramatic rise in popularity for remote-
sensing image acquisition and analysis in recent years. It has brought promising results in …
sensing image acquisition and analysis in recent years. It has brought promising results in …
Scalable multi-temporal remote sensing change data generation via simulating stochastic change process
Understanding the temporal dynamics of Earth's surface is a mission of multi-temporal
remote sensing image analysis, significantly promoted by deep vision models with its fuel …
remote sensing image analysis, significantly promoted by deep vision models with its fuel …
Temporal-agnostic change region proposal for semantic change detection
Remote sensing imagery allows temporal and large-scale observation of the Earth, and
advanced techniques such as deep learning have been developed to deal with the massive …
advanced techniques such as deep learning have been developed to deal with the massive …
Changemamba: Remote sensing change detection with spatio-temporal state space model
Convolutional neural networks (CNN) and Transformers have made impressive progress in
the field of remote sensing change detection (CD). However, both architectures have their …
the field of remote sensing change detection (CD). However, both architectures have their …
[PDF][PDF] 深度学习的遥感变化检测综述: 文献计量与分析
杨彬， 毛银， 陈晋， 刘建强， 陈杰， 闫凯 - 遥感学报, 2023 - ygxb.ac.cn
遥感变化检测可以获取地表变化信息, 对于理解人与自然相互作用, 推动可持续发展具有重要
意义. 随着遥感成像技术的提升和计算机科学的快速发展, 高光谱, 高时间, 高空间分辨率的遥感 …
意义. 随着遥感成像技术的提升和计算机科学的快速发展, 高光谱, 高时间, 高空间分辨率的遥感 …
ChangeCLIP: Remote sensing change detection with multimodal vision-language representation learning
Remote sensing change detection (RSCD), which aims to identify surface changes from
bitemporal images, is significant for many applications, such as environmental protection …
bitemporal images, is significant for many applications, such as environmental protection …
Detecting building changes using multi-modal Siamese multi-task networks from very high resolution satellite images
Two main issues are faced when using very-high-spatial-resolution (VHR) satellite images
for building change detection: 1) the boundaries of detected changes are hard to be …
for building change detection: 1) the boundaries of detected changes are hard to be …