17 May 2006 Performance measures for ATR systems with multiple classifiers and multiple labels
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Significant advances in the performance of ATR systems can be made when fusing individual classification systems into a single combined classification system. Often, these individual systems are dependent, or correlated, with one another. Additionally, these systems typically assume that two outcome labels, (for instance "target" and "non-target") exist. Little is known about the performance of fused classification systems when multiple outcome labels are used. In this paper, we propose a methodology for quantifying the performance of the fused classifier system using multiple labels. Specifically, a performance measure for a fused classification system using two classifiers and multiple labels will be developed. The performance measure developed is based on the Receiver Operating Characteristic (ROC) curve. The ROC curve in a two-label system has been well defined and used extensively, in not only ATR applications, but also other engineering and biomedical applications. A ROC manifold is defined and use in order to incorporate the multiple labels. An example of this performance measure for a given fusion rule and multiple labels is given.
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Christine M. Schubert, Christine M. Schubert, Steven Thorsen, Steven Thorsen, Mark E. Oxley, Mark E. Oxley, Kenneth W. Bauer, Kenneth W. Bauer, } "Performance measures for ATR systems with multiple classifiers and multiple labels", Proc. SPIE 6235, Signal Processing, Sensor Fusion, and Target Recognition XV, 62350V (17 May 2006); doi: 10.1117/12.668464; https://doi.org/10.1117/12.668464

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