Remote sensing image change detection (CD) is done to identify desired significant
changes between bitemporal images. Given two co-registered images taken at different …

Change detection (CD) aims to identify surface changes from bitemporal images. In recent
years, deep learning (DL)-based methods have made substantial breakthroughs in the field …

Remote sensing image change detection is the key to understanding surface changes.
Although the existing change detection methods have achieved good results, some …

The neural network-based remote sensing image change detection method faces a large
amount of imaging interference and severe class imbalance problems under high-resolution …

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 …

For change detection in remote sensing, constructing a training dataset for deep learning
models is quite difficult due to the requirements of bi-temporal supervision. To overcome this …

Traditional change detection (CD) methods operate in the simple image domain or hand-
crafted features, which has less robustness to the inconsistencies (eg, brightness and noise …

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 …

As an important task in the field of remote sensing (RS) image processing, RS image
change detection (CD) has made significant advances through the use of convolutional …

Change detection (CD) of remote sensing (RS) images is mushrooming up accompanied by
the on-going innovation of convolutional neural networks (CNNs). Yet with the high-speed …