Deep learning-based change detection in remote sensing images: A review
Images gathered from different satellites are vastly available these days due to the fast
development of remote sensing (RS) technology. These images significantly enhance the …
development of remote sensing (RS) technology. These images significantly enhance the …
Land-use/land-cover change detection based on a Siamese global learning framework for high spatial resolution remote sensing imagery
Due to the abundant features of high spatial resolution (HSR) remote sensing images,
change detection of these images is crucial to understanding the land-use and land-cover …
change detection of these images is crucial to understanding the land-use and land-cover …
A deeply supervised attention metric-based network and an open aerial image dataset for remote sensing change detection
Change detection (CD) aims to identify surface changes from bitemporal images. In recent
years, deep learning (DL)-based methods have made substantial breakthroughs in the field …
years, deep learning (DL)-based methods have made substantial breakthroughs in the field …
A survey on deep learning-based change detection from high-resolution remote sensing images
H Jiang, M Peng, Y Zhong, H Xie, Z Hao, J Lin, X Ma… - Remote Sensing, 2022 - mdpi.com
Change detection based on remote sensing images plays an important role in the field of
remote sensing analysis, and it has been widely used in many areas, such as resources …
remote sensing analysis, and it has been widely used in many areas, such as resources …
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 …
DASNet: Dual attentive fully convolutional Siamese networks for change detection in high-resolution satellite images
Change detection is a basic task of remote sensing image processing. The research
objective is to identify the change information of interest and filter out the irrelevant change …
objective is to identify the change information of interest and filter out the irrelevant change …
Optical remote sensing image change detection based on attention mechanism and image difference
X Peng, R Zhong, Z Li, Q Li - IEEE Transactions on Geoscience …, 2020 - ieeexplore.ieee.org
This study presents a new end-to-end change detection network, called difference-
enhancement dense-attention convolutional neural network (DDCNN), that is designed for …
enhancement dense-attention convolutional neural network (DDCNN), that is designed for …
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 …
Machine learning paradigm for structural health monitoring
Structural health diagnosis and prognosis is the goal of structural health monitoring.
Vibration-based structural health monitoring methodology has been extensively …
Vibration-based structural health monitoring methodology has been extensively …