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A Aerial Images Segmentation Method Based on Rough Sets and Neural Networks

机译:基于粗糙集和神经网络的航空影像分割方法

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The problem of aerial image segmentation using Rough sets and neural networks has been considered. Integrating the advantages of two approaches, this paper presents a hybrid system different from those previous works where rough sets were used only for accelerating or simplifying the process of using neural networks for aerial image segmentation.The lybrid system have been advanced to improve its performance or to explore new structures.These new segmentation algorithms avoids the difficulty of extracting rules from a trained neural network and possesses the robustness which are lacking for rough set based approaches.The proposed schemes are tested comparatively on a bank of test images as well as real world images.
机译:已经考虑了使用粗糙集和神经网络进行航空图像分割的问题。结合两种方法的优势,本文提出了一种混合系统,与以前的工作不同,后者仅将粗糙集用于加速或简化使用神经网络进行航空图像分割的过程。这些新的分割算法避免了从训练有素的神经网络提取规则的困难,并且具有基于粗糙集的方法所缺乏的鲁棒性。图片。

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