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Neural networks for automatic target recognition
Neural Networks, 1995Abstract Many applications reported in artificial neural networks are associated with military problems. This paper reviews concepts associated with the processing of military data to find and recognize targets—automatic target recognition (ATR). A general-purpose automatic target recognition system does not exist.
Steven K Rogers, John Colombi
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Image Matting for Automatic Target Recognition
IEEE Transactions on Aerospace and Electronic Systems, 2017Features used in the classification of targets are generally based on the shape or gray-level information of the preprocessed target chip. Consequently, the performance of an automatic target recognition (ATR) system critically depends on the preprocessing result.
Hyun-Woong Cho +3 more
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Automatic Target Recognition for Passive Radar
IEEE Transactions on Aerospace and Electronic Systems, 2014Air-traffic controllers cannot identify air vehicles flying with a defective or nonexistent transponder. Primary radar does not help, because it cannot classify air vehicles from echoes. Passive radar offers a potential solution, the main difficulty lying in the analysis of the data.
Jonathan Pisane +3 more
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High performance automatic target recognition
AFRICON 2015, 2015Designing a vision system, which was motivated by that of the human eye, has been done since the introduction of digital computing devices. Its computational complexity hinders it from the required accuracy and flexibility achievable by these systems.
Misiker Tadesse Aga, Eneyew Adugna
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Automatic Target Recognition with Dynamic Reconfiguration
Journal of VLSI signal processing systems for signal, image and video technology, 2000This paper describes the acceleration of an infrared automatic target recognition (IR ATR) application with a co-processor board that contains multiple field programmable gate array (FPGA) chips. Template and pixel level parallelism is exploited in an FPGA design for the bottleneck portion of the application.
Jack S. N. Jean +4 more
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Fusion techniques for automatic target recognition
32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings., 2004In this paper, we investigate several fusion techniques for designing a composite classifier to improve the performance (probability of correct classification) of FLIR ATR. In this research, we propose to use four ATR algorithms for fusion. The individual performance of the four contributing algorithms ranges from 73.5% to about 77% of probability of ...
Syed A. Rizvi, Nasser M. Nasrabadi
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Automatic target recognition using a neocognitron
IEEE Transactions on Knowledge and Data Engineering, 1992The use of a neocognitron in an automatic target recognition (ATR) system is described. An image is acquired, edge detected, segmented, and centered on a log-spiral grid using subsystems not discussed in the paper. A conformal transformation is used to map the log-spiral grid to a computation plane in which rotations and scalings are transformed to ...
Glenn S. Himes, Rafael M. Inigo
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Unification of Automatic Target Tracking and Automatic Target Recognition
SPIE Proceedings, 2014The subject being addressed is how an automatic target tracker (ATT) and an automatic target recognizer (ATR) can be fused together so tightly and so well that their distinctiveness becomes lost in the merger. This has historically not been the case outside of biology and a few academic papers.
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