双频ATR用于前视红外图像

Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (CVBVS'99) Pub Date : 1999-06-21 DOI:10.1109/CVBVS.1999.781091

P. Dainty, J. Boyce, C. Dimitropoulos, P. Edmundson, D. Toulson, M. Bernhardt

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引用次数: 5

摘要

利用两个波段的前视红外数据，从三个方面对目标识别和跟踪进行了评估。在跟踪环路中嵌入带有卡尔曼滤波器的相关器和神经网络，可以提高真实识别率，减少错误识别率。通过k近邻算法压缩可以减少大型训练集，而不会显著损失网络性能。结合来自两个波段的信息的系统仅比最佳的单波段信道略有改善。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Dual-band ATR for forward-looking infrared images

Three aspects of object recognition and tracking are evaluated on forward-looking infrared data from two wavebands. The combination of a correlator with a Kalman filter and a neural network embedded within the tracking loop is shown to increase true recognitions and decrease false recognitions. Large training sets may be reduced by condensing via a k-nearest-neighbour algorithm without significant loss of network performance. Systems combining information from the two wavebands show only a slight improvement over the best single band channel.

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来源期刊

Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (CVBVS'99)

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