Land-use land-cover classification by machine learning classifiers for satellite observations—A review
Rapid and uncontrolled population growth along with economic and industrial development,
especially in developing countries during the late twentieth and early twenty-first centuries …
especially in developing countries during the late twentieth and early twenty-first centuries …
A critical synthesis of remotely sensed optical image change detection techniques
State of the art reviews of remote sensing change detection are becoming increasingly
complicated and disparate due to an ever growing list of techniques, algorithms and …
complicated and disparate due to an ever growing list of techniques, algorithms and …
GETNET: A general end-to-end 2-D CNN framework for hyperspectral image change detection
Change detection (CD) is an important application of remote sensing, which provides timely
change information about large-scale Earth surface. With the emergence of hyperspectral …
change information about large-scale Earth surface. With the emergence of hyperspectral …
Remote sensing image change captioning with dual-branch transformers: A new method and a large scale dataset
Analyzing land cover changes with multitemporal remote sensing (RS) images is crucial for
environmental protection and land planning. In this article, we explore RS image change …
environmental protection and land planning. In this article, we explore RS image change …
Change-agent: Towards interactive comprehensive remote sensing change interpretation and analysis
Monitoring changes in the Earth's surface is crucial for understanding natural processes and
human impacts, necessitating precise and comprehensive interpretation methodologies …
human impacts, necessitating precise and comprehensive interpretation methodologies …
Change detection based on deep feature representation and mapping transformation for multi-spatial-resolution remote sensing images
Multi-spatial-resolution change detection is a newly proposed issue and it is of great
significance in remote sensing, environmental and land use monitoring, etc. Though multi …
significance in remote sensing, environmental and land use monitoring, etc. Though multi …
Change detection in hyperspectral images using recurrent 3D fully convolutional networks
Hyperspectral change detection (CD) can be effectively performed using deep-learning
networks. Although these approaches require qualified training samples, it is difficult to …
networks. Although these approaches require qualified training samples, it is difficult to …
Change guiding network: Incorporating change prior to guide change detection in remote sensing imagery
The rapid advancement of automated artificial intelligence algorithms and remote sensing
instruments has benefited change detection (CD) tasks. However, there is still a lot of space …
instruments has benefited change detection (CD) tasks. However, there is still a lot of space …
A CNN framework with slow-fast band selection and feature fusion grouping for hyperspectral image change detection
X Ou, L Liu, B Tu, G Zhang, Z Xu - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Change detection approaches can detect changed areas of the same scene at different
times. Hyperspectral remote-sensing images contain large amounts of spectral information …
times. Hyperspectral remote-sensing images contain large amounts of spectral information …
Feature-level change detection using deep representation and feature change analysis for multispectral imagery
Due to the noise interference and redundancy in multispectral images, it is promising to
transform the available spectral channels into a suitable feature space for relieving noise …
transform the available spectral channels into a suitable feature space for relieving noise …