Results 211 to 220 of about 11,957 (239)
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Proceedings of the IEEE, 1996
We describe an experimental, model-based automatic target recognition (ATR) system, called XTRS, for recognizing tactical vehicles in real or synthetic laser-radar (LADAR) range and intensity images corresponding to a forwardlooking, CO/sub 2/ laser radar (LADAR) that is carried either on a ground vehicle or on an airborne platform.
Jacques G. Verly, Richard L. Delanoy
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We describe an experimental, model-based automatic target recognition (ATR) system, called XTRS, for recognizing tactical vehicles in real or synthetic laser-radar (LADAR) range and intensity images corresponding to a forwardlooking, CO/sub 2/ laser radar (LADAR) that is carried either on a ground vehicle or on an airborne platform.
Jacques G. Verly, Richard L. Delanoy
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2003
Abstract : This report investigates evolutionary computational techniques such as genetic programming (GP), coevolutionary genetic programming (CGP), linear genetic programming (LGP) and genetic algorithms (GA) to automate the synthesis and analysis of object detection and recognition systems.
Krzysztof Krawiec +2 more
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Abstract : This report investigates evolutionary computational techniques such as genetic programming (GP), coevolutionary genetic programming (CGP), linear genetic programming (LGP) and genetic algorithms (GA) to automate the synthesis and analysis of object detection and recognition systems.
Krzysztof Krawiec +2 more
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SPIE Proceedings, 2009
We have continued to develop the Grayscale Optical Correlator (GOC) system and have explored a variety of automatic target recognition (ATR) applications to take advantage of the inherent performance advantages of the GOC vast parallelism and high-speed [1-4]. Recently, we have added a neural network (NN) post-processor to greatly decrease the false
Tien-Hsin Chao, Thomas Lu
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We have continued to develop the Grayscale Optical Correlator (GOC) system and have explored a variety of automatic target recognition (ATR) applications to take advantage of the inherent performance advantages of the GOC vast parallelism and high-speed [1-4]. Recently, we have added a neural network (NN) post-processor to greatly decrease the false
Tien-Hsin Chao, Thomas Lu
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Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) Parametric Study
2003Abstract : SAR ATR is a very complex problem that still has not been mastered. SAR ATR is difficult largely due to the fact that SAR imagery exhibits large variability. SAR imagery is a function of many variables called operating conditions (OCs) that can be subdivided into three large groups.
Sam Sink, Kefu Xue
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Diffusion Maps and Geometric Harmonics for Automatic Target Recognition (ATR). Volume 2. Appendices
2007Abstract : Geometric harmonics provides a framework for taking data in high-dimensional measurement spaces and embedding them in low dimensional Euclidean space according to a similarity measure. Euclidean coordinates then characterize the "manifold" on (or near) which the data live.
Ronald Coifman, Steven W. Zucker
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2000
Abstract : This report focuses on the development of an automatic target recognition (ATR) system using high resolution synthetic aperture radar (SAR) imagery. The system achieves 95 to 100 percent recognition rates when applied to a set of MSTAR images.
Tsung-Liang Chen, Thomas O. Binford
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Abstract : This report focuses on the development of an automatic target recognition (ATR) system using high resolution synthetic aperture radar (SAR) imagery. The system achieves 95 to 100 percent recognition rates when applied to a set of MSTAR images.
Tsung-Liang Chen, Thomas O. Binford
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2001 CIE International Conference on Radar Proceedings (Cat No.01TH8559), 2002
This paper firstly presents a concise and physically relevant parametric model for use in automatic target recognition (ATR), data compression and scattering studies. Then, the extraction algorithm of high-resolution target feature vectors for ATR in the presence of colored Gaussian noise is developed, which is not restricted by the low SNR and ...
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This paper firstly presents a concise and physically relevant parametric model for use in automatic target recognition (ATR), data compression and scattering studies. Then, the extraction algorithm of high-resolution target feature vectors for ATR in the presence of colored Gaussian noise is developed, which is not restricted by the low SNR and ...
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2005
Abstract : "Feature Extraction using Attributed Scattering Center Models for Model-Based Automatic Target Recognition." The primary research goal of the program was to develop fundamental understanding and advanced signal processing techniques for feature extraction to support feature-based automatic target recognition (ATR) systems employing synthetic
Inder J. Gupta +2 more
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Abstract : "Feature Extraction using Attributed Scattering Center Models for Model-Based Automatic Target Recognition." The primary research goal of the program was to develop fundamental understanding and advanced signal processing techniques for feature extraction to support feature-based automatic target recognition (ATR) systems employing synthetic
Inder J. Gupta +2 more
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2001
Abstract : The overall goal of the Electro-Optic Identification (EOID) Research Program is to support the performance of EOID sensors transitioning to the fleet. EOID is used in the identification of Mine Like Objects (MLOs) and is a pressing need for Mine Countermeasures (MCM) operations.
Mary C. Hulgan, James S. Taylor
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Abstract : The overall goal of the Electro-Optic Identification (EOID) Research Program is to support the performance of EOID sensors transitioning to the fleet. EOID is used in the identification of Mine Like Objects (MLOs) and is a pressing need for Mine Countermeasures (MCM) operations.
Mary C. Hulgan, James S. Taylor
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2015
Synthetic aperture radar (SAR) image classification is one of the challenging problems because of the difficult characteristics of SAR images. In this chapter, we implement SAR image classification on three military vehicles types, i.e., T72 tank, BMP2 armored personnel carriers (APCs), and BTR70 APCs.
Sansanee Auephanwiriyakul +2 more
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Synthetic aperture radar (SAR) image classification is one of the challenging problems because of the difficult characteristics of SAR images. In this chapter, we implement SAR image classification on three military vehicles types, i.e., T72 tank, BMP2 armored personnel carriers (APCs), and BTR70 APCs.
Sansanee Auephanwiriyakul +2 more
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