Neural techniques for image segmentation

M. Marsella, S. Miranda
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引用次数: 5

Abstract

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.
图像分割的神经技术
我们提出了新的神经技术,包括无监督技术和模糊逻辑基础。我们实现了一个混合神经网络,并应用了我们专门为它开发的三种不同的无监督学习算法:模糊MLSOM、模糊分层“神经气体”和模糊分层“最大熵”。所提出的实验处理图像分割问题。结果表明,神经网络是一种有效的图像处理和形状识别工具。
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