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 …
Beyond supervised learning in remote sensing: A systematic review of deep learning approaches
An increasing availability of remote sensing data in the era of geo big-data makes producing
well-represented, reliable training data to be more challenging and requires an excessive …
well-represented, reliable training data to be more challenging and requires an excessive …
Near real-time wildfire progression monitoring with Sentinel-1 SAR time series and deep learning
In recent years, the world witnessed many devastating wildfires that resulted in destructive
human and environmental impacts across the globe. Emergency response and rapid …
human and environmental impacts across the globe. Emergency response and rapid …
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 …
A survey of change detection methods based on remote sensing images for multi-source and multi-objective scenarios
Y You, J Cao, W Zhou - Remote Sensing, 2020 - mdpi.com
Quantities of multi-temporal remote sensing (RS) images create favorable conditions for
exploring the urban change in the long term. However, diverse multi-source features and …
exploring the urban change in the long term. However, diverse multi-source features and …
Unsupervised change detection by cross-resolution difference learning
X Zheng, X Chen, X Lu, B Sun - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Change detection (CD) aims to identify the differences between multitemporal images
acquired over the same geographical area at different times. With the advantages of …
acquired over the same geographical area at different times. With the advantages of …
Unsupervised change detection in multitemporal VHR images based on deep kernel PCA convolutional mapping network
With the development of Earth observation technology, a very-high-resolution (VHR) image
has become an important data source of change detection (CD). These days, deep learning …
has become an important data source of change detection (CD). These days, deep learning …
A multiscale self-attention deep clustering for change detection in SAR images
Synthetic aperture radar (SAR) image change detection (CD) is an important application in
the field of remote sensing. Due to the lack of labeled data especially in the pixelwise task, it …
the field of remote sensing. Due to the lack of labeled data especially in the pixelwise task, it …
Triple Change Detection Network via Joint Multi-Frequency and Full-Scale Swin-Transformer for Remote Sensing Images
Although deep learning-based change detection (CD) methods achieve great success in
remote sensing images, they still suffer from two main challenges. First, popular …
remote sensing images, they still suffer from two main challenges. First, popular …
Toward generalized change detection on planetary surfaces with convolutional autoencoders and transfer learning
Ongoing planetary exploration missions are returning large volumes of image data.
Identifying surface changes in these images, eg, new impact craters, is critical for …
Identifying surface changes in these images, eg, new impact craters, is critical for …