Topology representing networks
Neural Networks
A Self-Organizing Network that Can Follow Non-stationary Distributions
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
Hand Gesture Recognition Following the Dynamics of a Topology-Preserving Network
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Three-dimensional surface reconstruction using meshing growing neural gas (MGNG)
The Visual Computer: International Journal of Computer Graphics
A Neural Network Approach for Video Object Segmentation in Traffic Surveillance
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Automatic landmarking of 2d medical shapes using the growing neural gas network
CVBIA'05 Proceedings of the First international conference on Computer Vision for Biomedical Image Applications
Grayscale images and RGB video: compression by morphological neural network
ANNPR'12 Proceedings of the 5th INNS IAPR TC 3 GIRPR conference on Artificial Neural Networks in Pattern Recognition
A self-organizing map for traffic flow monitoring
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advences in computational intelligence - Volume Part II
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This paper aims to address the ability of self-organizing neural network models to manage video and image processing in real-time. The Growing Neural Gas networks (GNG) with its attributes of growth, flexibility, rapid adaptation, and excellent quality representation of the input space makes it a suitable model for real time applications. A number of applications are presented that includes: image compression, hand and medical image contours representation, surveillance systems, hand gesture recognition systems or 3D data reconstruction.