This study presents a new end-to-end change detection network, called difference-
enhancement dense-attention convolutional neural network (DDCNN), that is designed for …

Change detection (CD) in optical remote sensing images has significantly benefited from the
development of deep convolutional neural networks (CNNs) due to their strong capability of …

Accurate change detection in optical aerial images by using deep learning techniques has
been attracting lots of research efforts in recent years. Correct change-detection results …

In this article, a remote sensing image change detection method based on depthwise
separable convolution with U-Net is proposed, which omits the tedious steps of generating …

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

With the development of deep learning techniques in the field of remote sensing change
detection, many change detection algorithms based on convolutional neural networks …

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 …

Remote sensing image change detection plays an important role in urban planning and
environmental monitoring. However, the existing change detection algorithms have limited …

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

Considering the lack of labeled training data sets for the supervised change detection task,
in this letter, we try to relieve this problem by proposing a convolutional neural network …