Change detection based on artificial intelligence: State-of-the-art and challenges
Change detection based on remote sensing (RS) data is an important method of detecting
changes on the Earth's surface and has a wide range of applications in urban planning …
changes on the Earth's surface and has a wide range of applications in urban planning …
Deep learning for change detection in remote sensing: a review
ABSTRACT A large number of publications have incorporated deep learning in the process
of remote sensing change detection. In these Deep Learning Change Detection (DLCD) …
of remote sensing change detection. In these Deep Learning Change Detection (DLCD) …
End-to-end change detection for high resolution satellite images using improved UNet++
Change detection (CD) is essential to the accurate understanding of land surface changes
using available Earth observation data. Due to the great advantages in deep feature …
using available Earth observation data. Due to the great advantages in deep feature …
Change detection from very-high-spatial-resolution optical remote sensing images: Methods, applications, and future directions
Change detection is a vibrant area of research in remote sensing. Thanks to increases in the
spatial resolution of remote sensing images, subtle changes at a finer geometrical scale can …
spatial resolution of remote sensing images, subtle changes at a finer geometrical scale can …
Fully convolutional change detection framework with generative adversarial network for unsupervised, weakly supervised and regional supervised change detection
Deep learning for change detection is one of the current hot topics in the field of remote
sensing. However, most end-to-end networks are proposed for supervised change …
sensing. However, most end-to-end networks are proposed for supervised change …
Unsupervised multimodal change detection based on structural relationship graph representation learning
Unsupervised multimodal change detection is a practical and challenging topic that can play
an important role in time-sensitive emergency applications. To address the challenge that …
an important role in time-sensitive emergency applications. To address the challenge that …
Unsupervised image regression for heterogeneous change detection
Change detection in heterogeneous multitemporal satellite images is an emerging and
challenging topic in remote sensing. In particular, one of the main challenges is to tackle the …
challenging topic in remote sensing. In particular, one of the main challenges is to tackle the …
Deep image translation with an affinity-based change prior for unsupervised multimodal change detection
Image translation with convolutional neural networks has recently been used as an
approach to multimodal change detection. Existing approaches train the networks by …
approach to multimodal change detection. Existing approaches train the networks by …
Code-aligned autoencoders for unsupervised change detection in multimodal remote sensing images
LT Luppino, MA Hansen… - … on Neural Networks …, 2022 - ieeexplore.ieee.org
Image translation with convolutional autoencoders has recently been used as an approach
to multimodal change detection (CD) in bitemporal satellite images. A main challenge is the …
to multimodal change detection (CD) in bitemporal satellite images. A main challenge is the …
[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 …