Paper
17 May 2006 Performance measures for ATR systems with multiple classifiers and multiple labels
Author Affiliations +
Abstract
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.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christine M. Schubert, Steven Thorsen, Mark E. Oxley, and Kenneth W. Bauer Jr. "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); https://doi.org/10.1117/12.668464
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Cited by 5 scholarly publications.
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KEYWORDS
Classification systems

Lithium

Automatic target recognition

Sensors

Receivers

Biomedical engineering

Biomedical optics

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