Neural techniques for image segmentation
M. Marsella, Sergio Miranda · 2002
We present new neural techniques including unsupervised technology and fuzzy logic foundations. We realized a hybrid neural network and applied three different unsupervised learning algorithms that we developed specially for it: fuzzy MLSOM, fuzzy hierarchical "neural gas" and fuzzy hierarchical "maximum entropy". The experiments presented deal with image segmentation. The results obtained show that neural networks are a valid instrument for image processing and shape recognition.