Pattern Recognition Letters - Special issue on non-conventional pattern analysis in remote sensing
Pattern Recognition Letters
An incremental—learning neural network for the classification of remote—sensing images
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
Pattern Recognition Letters
Neural maps in remote sensing image analysis
Neural Networks - 2003 Special issue: Neural network analysis of complex scientific data: Astronomy and geosciences
Segmentation of remote-sensing images by incremental neural network
Pattern Recognition Letters
Dynamic self-organizing maps with controlled growth for knowledge discovery
IEEE Transactions on Neural Networks
The growing hierarchical self-organizing map: exploratory analysis of high-dimensional data
IEEE Transactions on Neural Networks
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Image segmentation is a typical task in the field of image processing. There is a great number of image segmentation methods in the literature, but most of these methods are not suitable for multispectral images and they require a priori knowledge. In this work, a hierarchical self-organizing network is proposed for multispectral image segmentation. An advantage of the proposed neural model is due to the hierarchical architecture, which is more flexible in the adaptation process to input data. Experimental results show that the proposed approach is promising for multispectral image processing.