In recent years, building change detection has made remarkable progress through using
deep learning. The core problems of this technique are the need for additional data (eg …

In the field of remote sensing applications, semantic change detection (SCD) simultaneously
identifies changed areas and their change types by jointly conducting bitemporal image …

In recent years, building change detection methods have made great progress by
introducing deep learning, but they still suffer from the problem of the extracted features not …

Building change detection is a very important application in the field of remote sensing.
Recently, deep learning (DL) has been introduced to solve the change detection task and …

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

Change detection (CD) in remote sensing images is one of the most important technical
options to identify changes in observations in an efficient manner. CD has a wide range of …

Building change detection (BCD) plays a crucial role in urban planning and development
and has received extensive attention. However, existing deep learning-based change …

Building change detection in high-resolution satellite images plays a special role in urban
management and development. Recently, methods for building change detection have been …

Building change detection (BCD) for very-high-spatial-resolution (VHR) remote sensing
images is very important and challenging in the field of remote sensing, as the building is …

Building change detection (BCD) is significant for urban planning and environmental
protection. In view of the interclass similarity and intraclass difference of building changes in …