Artificial intelligence for remote sensing data analysis: A review of challenges and opportunities
Artificial intelligence (AI) plays a growing role in remote sensing (RS). Applications of AI,
particularly machine learning algorithms, range from initial image processing to high-level …
particularly machine learning algorithms, range from initial image processing to high-level …
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 …
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 …
Multiscale diff-changed feature fusion network for hyperspectral image change detection
For hyperspectral image (HSI) change detection (CD), multiscale features are usually used
to construct the detection models. However, the existing studies only consider the multiscale …
to construct the detection models. However, the existing studies only consider the multiscale …
A CNN-transformer network with multiscale context aggregation for fine-grained cropland change detection
Nonagriculturalization incidents are serious threats to local agricultural ecosystem and
global food security. Remote sensing change detection (CD) can provide an effective …
global food security. Remote sensing change detection (CD) can provide an effective …
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 …
Machine learning in modelling land-use and land cover-change (LULCC): Current status, challenges and prospects
Land-use and land-cover change (LULCC) are of importance in natural resource
management, environmental modelling and assessment, and agricultural production …
management, environmental modelling and assessment, and agricultural production …
A survey on deep learning-based change detection from high-resolution remote sensing images
H Jiang, M Peng, Y Zhong, H **e, 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 …
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 …