Results 201 to 210 of about 11,848 (250)
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Improved automatic target recognition (ATR) value through enhancements and accommodations
SPIE Proceedings, 2006There is a strong and growing need for automatic target recognition (ATR) technologies. Those technologies have made great strides; however, there is a general sense that they are not having the full impact desired. This paper develops a value-based framework for considering how ATR technology can be made more relevant and then introduces and ...
Timothy D. Ross, Lloyd C. Goodwon
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Geospatial feature based automatic target recognition (ATR) using data models
SPIE Proceedings, 2010We present a method for deriving an automatic target recognition (ATR) system using geospatial features and a Data Model populated decision architecture in the form of a self-organizing knowledge base. The goal is to derive an ATR that recognizes targets it has seen before while minimizing false alarms (zero false alarms). We present an investigation
Holger Jaenisch +9 more
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Multiresolution Framwork with Neural Network Approach for Automatic Target Recognition (ATR)
2009 International Conference on Signal Acquisition and Processing, 2009Automatic Target Recognition (ATR) is an approach by which we identify one or a group of target-objects in a scene. It plays a pivotal role in the challenging fields of defense and civil. Most of the methods in this context are based on fix window-size technique.
Dileep Kumar, Shirshu Varma
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Cascaded automatic target recognition (Cascaded ATR)
SPIE Proceedings, 2010The global war on terror has plunged US and coalition forces into a battle space requiring the continuous adaptation of tactics and technologies to cope with an elusive enemy. As a result, technologies that enhance the intelligence, surveillance, and reconnaissance (ISR) mission making the warfighter more effective are experiencing increased interest.
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SPIE Proceedings, 2001
This paper presents a general quantitative approach to performance evaluation of ATR systems, especially for FLIR imagery. The general quantitative evaluation approach we proposed consists of three main steps. First, multiple sets of testing image sequences with significantly varying difficulty for specific environment, which can be precisely measured,
Zhaoyang Chen, Guilin Zhang
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This paper presents a general quantitative approach to performance evaluation of ATR systems, especially for FLIR imagery. The general quantitative evaluation approach we proposed consists of three main steps. First, multiple sets of testing image sequences with significantly varying difficulty for specific environment, which can be precisely measured,
Zhaoyang Chen, Guilin Zhang
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Focus of attention (FOA) identification from compressed video for automatic target recognition (ATR)
Proceedings., International Conference on Image Processing, 2002We examine an approach to perform pattern recognition on compressed video such as MPEG data streams. The current effort has focused on the identification of the region of interest (ROI) which contains the target, which is also known as the focus of attention (FOA) module. Two techniques are studied, i.e.
null Jin Li +2 more
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A Unified Multiresolution Framework for Automatic Target Recognition (ATR)
2001Abstract : This report describes the development of multiscale, multiresolution methods for automatic target recognition (ATR). The methods are applied to and developed specifically for synthetic aperture radar data. Applications include high level reasoning over learned target models, information theoretic approaches for pose estimation, and model ...
Alan Willsky, Eric Grimson, John Fisher
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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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Feature and Extractor Evaluation Concepts for Automatic Target Recognition (ATR)
1995Abstract : This report develops concepts that will support the evaluation planning for the MSTAR features and feature extractors. These concepts will be used later in building a detailed evaluation plan. We began our development by distinguishing between the evaluation of a feature set and the evaluation of an extractor.
Robert B. Kotz +3 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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