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 …

Recent many researchers focus on image segmentation methods due to the rapid
development of artificial intelligence technology. Hereinto, pulse-coupled neural network …

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 …

Monitoring variations in the extent of wet snow over space and time is essential for many
applications, such as hydrology, mountain ecosystems, meteorology and avalanche …

Accurate segmentation of 3D medical images is vital for computer-aided diagnosis.
However, the complexity of target morphological variations and a scarcity of labeled data …

Improving the efficiency of current neural networks and modeling them on biological neural
systems have become prominent research directions in recent years. The pulse-coupled …

Pulse‐coupled neural network (PCNN) is a biologically‐inspired algorithm suited for image
processing. However, determining a set of parameters involved in the alteration of the neural …

In this paper, we propose a variational level set model for multiscale image segmentation
that can extract desired object from the background under various scales. The new model …

Unsupervised color image segmentation based on low level color features aims to assign
same label to all pixels of a region with color homogeneity, which underlies many higher …