聚类分析的一种新方法

2017 IEEE 4th International Conference Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD) Pub Date : 2017-10-01 DOI:10.1109/APUAVD.2017.8308815

V. Sineglazov, O. Chumachenko, V. Gorbatiuk

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引用次数: 0

摘要

提出了一种新的聚类方法，该方法能够找到被某些复杂超曲面分隔的聚类。该方法可用于对大量未标记图像进行分析，这些图像现在可以很容易地收集到，特别是通过使用装有摄像头的无人驾驶飞行器。该方法是基于“软化”初始聚类准则，然后使用非线性优化来寻找分离聚类的最优超曲面。

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A new approach in cluster analysis

A new clustering approach that is capable of finding clusters that are separated by some complex hypersurface is proposed. The approach can be useful for performing analysis of big amounts of unlabeled images that can be nowadays easily gathered, in particular by using unmanned aerial vehicle with mounted cameras. The approach is based on “softening” the initial clustering criterion and then using nonlinear optimization to find the optimal hypersurface that separates clusters.

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2017 IEEE 4th International Conference Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD)

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