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Rough Sets and Neural Networks Based Aerial Images Segmentation Method

机译:基于粗糙集和神经网络的航空图像分割方法

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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 hybrid 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,该系统不同于以前的工作,在粗糙系统中,粗糙集仅用于加速或简化使用神经网络进行航空图像分割的过程。改进了混合动力系统,以改善其性能或探索新的结构。这些新的分割算法避免了从训练有素的神经网络中提取规则的困难,并且具有基于粗糙集的方法所缺乏的鲁棒性。所提出的方案在一组测试图像以及真实世界图像上进行了比较测试。

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