基于AUC度量的序列前向特征选择红外小目标识别

2014 IEEE International Conference on Industrial Technology (ICIT) Pub Date : 2014-09-11 DOI:10.1109/ICIT.2014.6895005

Sungho Kim, Kyung-Tae Kim, So-Hyun Kim

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引用次数: 4

摘要

红外搜索与跟踪(IRST)是侦察和精确制导导弹军事应用中的一个重要研究课题。IRST算法的瓶颈是在现实应用中由于天空云、海面闪烁和地面杂波而产生的大量假警报。提出了一种基于AUC (area under ROC curve)度量的前向特征选择目标识别方法。在真实目标序列上的实验结果验证了该方法的可行性。

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Infrared small target discrimination using sequential forward feature selection with AUC mettric

Infrared search and track (IRST) is an important research topic in military applications in surveillance and precise guided missiles. The bottleneck of IRST algorithm is huge number of false alarms in real world applications due to sky cloud, sea-glints, and ground clutters. This paper presents a novel target discrimination method using forward feature selection with area under ROC curve (AUC) metric. Experimental results on real target sequences validate the feasibility of the proposed method.

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2014 IEEE International Conference on Industrial Technology (ICIT)

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