Advances in artificial intelligence (AI) techniques that can be used for different purposes
have enabled it to be used in many different industrial applications. These are mainly used …

We propose an unsupervised deep convolutional coupling network for change detection
based on two heterogeneous images acquired by optical sensors and radars on different …

Motion detection is the first essential process in the extraction of information regarding
moving objects and makes use of stabilization in functional areas, such as tracking …

This paper presents a novel background modeling and subtraction approach for video
object segmentation. A neural network (NN) architecture is proposed to form an …

To detect changed areas in multitemporal polarimetric synthetic aperture radar (SAR)
images, this paper presents a novel version of convolutional neural network (CNN), which is …

Remote sensing images are commonly used to monitor the earth surface evolution. This
surveillance can be conducted by detecting changes between images acquired at different …

Building change detection is important for urban area monitoring, disaster assessment and
updating geo-database. 3D information derived from image dense matching or airborne light …

Crosstalk phenomena taking place between synapses can influence signal transmission
and, in some cases, brain functions. It is thus important to discover the dynamic behaviors of …

Remotely sensed high-resolution satellite images contain various information in context of
changes. By analyzing this information very minutely, changes occurred in various …

The change-detection problem can be viewed as an unsupervised classification problem
with two classes corresponding to changed and unchanged areas. Image differencing is a …