Images gathered from different satellites are vastly available these days due to the fast
development of remote sensing (RS) technology. These images significantly enhance the …

Deep learning (DL) algorithms are considered as a methodology of choice for remote-
sensing image analysis over the past few years. Due to its effective applications, deep …

Change detection based on remote sensing images plays an important role in the field of
remote sensing analysis, and it has been widely used in many areas, such as resources …

Change detection is an essential and widely utilized task in remote sensing that aims to
detect and analyze changes occurring in the same geographical area over time, which has …

Supervised deep neural networks (DNNs) have been extensively used in diverse tasks.
Generally, training such DNNs with superior performance requires a large amount of labeled …

ABSTRACT A large number of publications have incorporated deep learning in the process
of remote sensing change detection. In these Deep Learning Change Detection (DLCD) …

Remote sensing is a tool of interest for a large variety of applications. It is becoming
increasingly more useful with the growing amount of available remote sensing data …

In their applications, both deep learning techniques and object-based image analysis (OBIA)
have shown better performance separately than conventional methods on change detection …

Change detection (CD) is one of the main applications of remote sensing. With the
increasing popularity of deep learning, most recent developments of CD methods have …

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 …