Results 121 to 130 of about 358 (157)
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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
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SPIE Proceedings, 2007
The US Air Force Research Laboratory (AFRL) is exploring the decision-level fusion (DLF) trade space in the Fusion for Identifying Targets Experiment (FITE) program. FITE is surveying past DLF approaches and experiments. This paper reports preliminary findings from that survey, which ultimately plans to place the various studies in a common framework ...
Erik Blasch, Timothy D Ross
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The US Air Force Research Laboratory (AFRL) is exploring the decision-level fusion (DLF) trade space in the Fusion for Identifying Targets Experiment (FITE) program. FITE is surveying past DLF approaches and experiments. This paper reports preliminary findings from that survey, which ultimately plans to place the various studies in a common framework ...
Erik Blasch, Timothy D Ross
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Geospatial feature based automatic target recognition (ATR) using data models
Proceedings of SPIE, 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 M Jaenisch, James W Handley
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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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Proceedings of SPIE, 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
Thomas Lu, Tien-Hsin Chao
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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
Thomas Lu, Tien-Hsin Chao
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LIDA-ATR for object detection in Automatic Target Recognition system
2014 International Conference on Electronics, Information and Communications (ICEIC), 2014Dong-Seong Kim
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Complete Solutions to an Automatic Target Recognition (ATR) Differential Game With Singular Surfaces
IEEE Transactions on Aerospace and Electronic Systems, 2023Zachariah Fuchs +2 more
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Advanced Automatic Target Recognition (ATR) with Infrared (IR) Sensors
2021 IEEE Aerospace Conference (50100), 2021Automatic Target Detection (ATD) and Recognition (ATR) are critical for video analysis and image understanding for many military and commercial applications deployed on satellites and UAV platforms. Infrared (IR) sensors can be used to detect targets during day and night time but there are few effective ATR algorithms that can exploit these sensors ...
Hai- Wen Chen +4 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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