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 …

Change detection (CD) in remote sensing (RS) imagery is a pivotal method for detecting
changes in the Earth's surface, finding wide applications in urban planning, disaster …

Change detection (CD) aims to identify the differences between multitemporal images
acquired over the same geographical area at different times. With the advantages of …

Deep-learning techniques have achieved great success in remote-sensing image change
detection. Most of them are supervised techniques, which usually require large amounts of …

Deep learning-based unsupervised change detection (CD) methods compare a prechange
and a postchange image in deep feature space and require precise knowledge of the event …

The use of deep learning (DL) methods for change detection (CD) is currently dominated by
supervised models that require a large number of labeled samples. However, these samples …

Heterogeneous bitemporal images have different visual appearances and inconsistent data
distribution for the same scene, making it challenging to detect changes, which need to align …

Deep transfer-learning-based change detection methods are dependent on the availability
of sensor-specific pretrained feature extractors. Such feature extractors are not always …

Deep learning techniques have achieved great success in remote sensing image change
detection. Most of them are supervised techniques, which usually require large amounts of …

Change detection from traditional 2D optical images has limited capability to model the
changes in the height or shape of objects. Change detection using 3D point cloud from …