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 …
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 …
Asymmetric siamese networks for semantic change detection in aerial images
Given two multitemporal aerial images, semantic change detection (SCD) aims to locate the
land-cover variations and identify their change types with pixelwise boundaries. This …
land-cover variations and identify their change types with pixelwise boundaries. This …
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 …
A deep convolutional coupling network for change detection based on heterogeneous optical and radar images
We propose an unsupervised deep convolutional coupling network for change detection
based on two heterogeneous images acquired by optical sensors and radars on different …
based on two heterogeneous images acquired by optical sensors and radars on different …
High-resolution SAR image classification via deep convolutional autoencoders
Synthetic aperture radar (SAR) image classification is a hot topic in the interpretation of SAR
images. However, the absence of effective feature representation and the presence of …
images. However, the absence of effective feature representation and the presence of …
Change detection in heterogenous remote sensing images via homogeneous pixel transformation
The change detection in heterogeneous remote sensing images remains an important and
open problem for damage assessment. We propose a new change detection method for …
open problem for damage assessment. We propose a new change detection method for …
Deep supervised and contractive neural network for SAR image classification
The classification of a synthetic aperture radar (SAR) image is a significant yet challenging
task, due to the presence of speckle noises and the absence of effective feature …
task, due to the presence of speckle noises and the absence of effective feature …
The time variable in data fusion: A change detection perspective
F Bovolo, L Bruzzone - IEEE Geoscience and Remote Sensing …, 2015 - ieeexplore.ieee.org
This paper presents an overview on the image fusion concept in the context of multitemporal
remote sensing image processing. In the remote sensing literature, multitemporal image …
remote sensing image processing. In the remote sensing literature, multitemporal image …
A new multivariate statistical model for change detection in images acquired by homogeneous and heterogeneous sensors
Remote sensing images are commonly used to monitor the earth surface evolution. This
surveillance can be conducted by detecting changes between images acquired at different …
surveillance can be conducted by detecting changes between images acquired at different …