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Back-Propagation and K-Means Algorithms Comparison

机译:反向传播和K均值算法比较

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摘要

The paper describes the application of algorithms for object classification by using artificial neural networks. The MLP (Multi Layer Perception) and RBF (Radial Basis Function) neural networks were used. We compared results obtained by a using of learning algorithms Back-Propagation (BP) and K-Means. The real technological scene for object classification was simulated with digitization of two-dimensional pictures. The principles and algorithms given below have been used in an application that was developed at Brno University of Technology.
机译:本文介绍了人工神经网络在对象分类算法中的应用。使用了MLP(多层感知)和RBF(径向基函数)神经网络。我们比较了通过使用学习算法反向传播(BP)和K均值获得的结果。利用二维图片的数字化模拟了用于对象分类的实际技术场景。下面给出的原理和算法已在布尔诺工业大学开发的应用程序中使用。

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