Image analysis for airborne reconnaissance and missile applications
Pattern Recognition Letters
Pattern Recognition Letters
Image Processing Using Pulse-Coupled Neural Networks
Image Processing Using Pulse-Coupled Neural Networks
MICRONEURO '99 Proceedings of the 7th International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems
Image thinning using pulse coupled neural network
Pattern Recognition Letters
A region-based multi-sensor image fusion scheme using pulse-coupled neural network
Pattern Recognition Letters
Letters: A class of binary images thinning using two PCNNs
Neurocomputing
Multi-focus image fusion using pulse coupled neural network
Pattern Recognition Letters
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03
Dual-channel PCNN and Its Application in the Field of Image Fusion
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 01
Feature Extraction using Unit-linking Pulse Coupled Neural Network and its Applications
Neural Processing Letters
Medical image fusion using m-PCNN
Information Fusion
Car plate localization using pulse coupled neural network in complicated environment
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Fingerprint classification by SPCNN and combined LVQ networks
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
An adaptive image segmentation method based on a modified pulse coupled neural network
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Binary Fingerprint Image Thinning Using Template-Based PCNNs
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Guest Editorial Overview Of Pulse Coupled Neural Network (PCNN) Special Issue
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Analog implementation of pulse-coupled neural networks
IEEE Transactions on Neural Networks
Physiologically motivated image fusion for object detection using a pulse coupled neural network
IEEE Transactions on Neural Networks
Perfect image segmentation using pulse coupled neural networks
IEEE Transactions on Neural Networks
Smart adaptive optic systems using spatial light modulators
IEEE Transactions on Neural Networks
Finding the shortest path in the shortest time using PCNN's
IEEE Transactions on Neural Networks
Object detection using pulse coupled neural networks
IEEE Transactions on Neural Networks
Foveation by a pulse-coupled neural network
IEEE Transactions on Neural Networks
Region growing with pulse-coupled neural networks: an alternative to seeded region growing
IEEE Transactions on Neural Networks
Simple model of spiking neurons
IEEE Transactions on Neural Networks
Pulse-coupled neural networks for contour and motion matchings
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Image shadow removal using pulse coupled neural network
IEEE Transactions on Neural Networks
Image fusion using self-constraint pulse-coupled neural network
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
Review: Pulse coupled neural networks and its applications
Expert Systems with Applications: An International Journal
Spiking cortical model for multifocus image fusion
Neurocomputing
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This paper reviews the research status of pulse-coupled neural networks (PCNN) in the past decade. Considering there are too many publications about the PCNN, we summarize main approaches and point out interesting parts of the PCNN researches rather than contemplate to go into details of particular algorithms or describe results of comparative experiments. First, the current status of the PCNN and some modified models are briefly introduced. Second, we review the PCNN applications in the field of image processing (e.g. image segmentation, image enhancement, image fusion, object and edge detection, pattern recognition, etc.), then applications in other fields also are mentioned. Subsequently, some existing problems are summarized, while we give some suggestions for the solutions to some puzzles. Finally, the trend of the PCNN is pointed out.