Two main issues are faced when using very-high-spatial-resolution (VHR) satellite images
for building change detection: 1) the boundaries of detected changes are hard to be …

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 this study, a Semi-Supervised Learning (SSL) method for improved urban change
detection from bi-temporal image pairs is presented. The proposed method employs a Dual …

Building change detection is a prominent topic in remote sensing applications. Scholars
have proposed a variety of fully-convolutional-network-based change detection methods for …

In recent years, using deep learning for large area building change detection has proven to
be very efficient. However, the current methods for pixel-wise building change detection still …

Buildings can represent the process of urban development, and building change detection
can support land use management and urban planning. However, existing building change …

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 (BCD) recently can be handled well under the booming of deep-
learning based computer vision techniques. However, segmentation and recognition for …

Building change detection is a primary task in the application of remote sensing images,
especially in city land resource management and urbanization process assesment. Due to …

Although considerable success has been achieved in change detection on optical remote
sensing images, accurate detection of specific changes is still challenging. Due to the …