This paper surveys recent advances in pulse-coupled neural networks (PCNNs) and their
applications in image processing. The PCNN is a neurology-inspired neural network model …

Pulse-coupled neural networks (PCNN) have an inherent ability to process the signals
associated with the digital visual images because it is inspired from the neuronal activity in …

Spiking neural networks (SNNs) are a promising energy-efficient alternative to artificial
neural networks (ANNs) due to their rich dynamics, capability to process spatiotemporal …

Medical image fusion has many applications to healthcare that is accomplished by
extracting and then combining the complementary information from multiple medical images …

One of the processes occurs in the visual cortex, which is the part of the brain that receives
information from the eye. At this point in the system the eye has already processed and …

An automatic parameter setting method of a simplified pulse coupled neural network
(SPCNN) is proposed here. Our method successfully determines all the adjustable …

The issue of visible light and infrared images fusion has been an active topic in both military
and civilian areas, and a great many relevant algorithms and techniques have been …

The aim of medical image fusion is to improve the clinical diagnosis accuracy, so the fused
image is generated by preserving salient features and details of the source images. This …

In this paper, structure elements' descriptor (SED)–a novel texture descriptor, is proposed.
SED can effectively describe images and represent image local features. Moreover, SED …

In this paper, without separating complex-valued neural networks into two real-valued
systems, the finite-time synchronization is addressed for a class of fully complex-valued …