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Improvement of Plastic Landmine Visualization Performance by Use of Ring-CSOM and Frequency-Domain Local Correlation

机译:通过使用环形CSOM和频域局部相关性改善塑料地雷的可视化性能

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摘要

The complex-valued self-organizing map (CSOM) realizes an adaptive distinction between plastic landmines and other objects in landmine visualization systems. However, when the spatial resolution in electromagnetic-wave measurement is not sufficiently high, the distinction sometimes fails. To solve this problem, in this paper, we propose two techniques to enhance the visualization ability. One is the utilization of SOM-space topology in the CSOM adaptive classification. The other is a novel feature extraction method paying attention to local correlation in the frequency domain. In experimental results, we find that these two techniques significantly improve the visualization performance. The local-correlation method contributes also to the reduction of the number of tuning parameters in the CSOM classification.
机译:复数值自组织图(CSOM)实现了塑料地雷与地雷可视化系统中其他对象之间的自适应区别。然而,当电磁波测量中的空间分辨率不够高时,区分有时会失败。为了解决这个问题,本文提出了两种增强可视化能力的技术。一种是在CSOM自适应分类中利用SOM空间拓扑。另一种是新颖的特征提取方法,其关注频域中的局部相关性。在实验结果中,我们发现这两种技术显着提高了可视化性能。局部相关方法还有助于减少CSOM分类中的调整参数数量。

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