Recent Advances in Pulse-Coupled Neural Networks with Applications in Image Processing

• DOI: 10.3390/electronics11203264
• Publication Date: 2022-10-12T02:18:13Z
• Authors: Haoran Liu; Mingzhe Liu; Dongfen Li; Wenfeng Zheng; Lirong Yin; Ruili Wang
• Keywords: Schematic

This paper surveys recent advances in pulse-coupled neural networks (PCNNs) and their applications image processing. The PCNN is a neurology-inspired network model that aims to imitate the information analysis process of biological cortex. In years, many PCNN-derived models have been developed. Research with respect these can be divided into three categories: (1) reduce number manual parameters, (2) achieve better real cortex imitation performance, (3) combine them other methodologies. We provide comprehensive schematic review novel models. Moreover, has widely used processing field due its outstanding extraction ability. processing, providing general framework for state art understanding PCNNs conclusion, are developing rapidly, it projected more emerging will seen future.