Change detection (CD) aims to distinguish surface changes based on bitemporal images.
Since high-resolution (HR) images cannot be typically acquired continuously over time …

Change detection (CD), as one of the central problems in Earth observation, has attracted a
lot of research interest over recent decades. Due to the rapid development of satellite …

Change detection (CD) based on high-resolution remote sensing images can be used to
monitor land cover changes, which is an important and challenging topic in the remote …

The popular Siamese convolutional neural networks (CNNs) for remote sensing (RS) image
change detection (CD) often suffer from two problems. First, they either ignore the original …

Detecting changes using bitemporal remote sensing imagery is vital to understand the
dynamics of the land surface. Existing change detection models based on deep learning …

Extracting change regions from bitemporal images is crucial to urban planning, land, and
resources survey. In the literature, many methods obtaining difference between bitemporal …

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 …

Change detection methods can achieve high learning ability and recognition accuracy with
the introduction of deep convolutional neural networks, but due to the influence of the …

Change detection (CD) remains an important issue in remote sensing applications,
especially for high-resolution images, but it has yet to be fully resolved. In this study, we …

While deep learning-based methods have gained considerable improvements in remote
sensing (RS) image change detection (CD), scale variations and pseudochanges hinder …