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检索条件"任意字段=Multisensor. Multisource Information Fusion: Architectures, Algorithms, and Applications 2003"

共 284 条记录，以下是51-60 订阅

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Reliable sources and uncertain decisions in multisensor.systems

Reliable sources and uncertain decisions in multisensor syst...

引用

Conference on multisensor. multisource information fusion - architectures, algorithms, and applications

作者： Minor, Christian Johnson, Kevin Nova Res Inc Alexandria VA 22308 USA Naval Res Lab Washington DC 20375 USA

ISBN: (纸本)9781628416145

Conflict among information sources is a feature of fused multisource and multisensor.systems. Accordingly, the subject of conflict resolution has a long history in the literature of data fusion algorithms such as that of Dempster-Shafer theory (DS). Most conflict resolution strategies focus on distributing the conflict among the elements of the frame of discernment (the set of hypotheses that describe the possible decisions for which evidence is obtained) through rescaling of the evidence. These "closed-world" strategies imply that conflict is due to the uncertainty in evidence sources stemming from their reliability. An alternative approach is the "open-world" hypothesis, which allows for the presence of "unknown" elements not included in the original frame of discernment. Here, conflict must be considered as a result of uncertainty in the frame of the discernment, rather than solely the province of evidence sources. Uncertainty in the operating environment of a fused system is likely to appear as an open-world scenario. Understanding the origin of conflict (source versus frame of discernment uncertainty) is a challenging area for research in fused systems. Determining the ratio of these uncertainties provides useful insights into the operation of fused systems and confidence in their decisions for a variety of operating environments. Results and discussion for the computation of these uncertainties are presented for several combination rules with simulated data sets.

关键词： multisensor.systems data fusion sensor reliability interferants open-world sensing Dempster-Shafer theory combination rules

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Multi-channel nonlinear phase analysis for time frequency data fusion

Multi-channel nonlinear phase analysis for time frequency da...

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Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2003

作者： Mavandadi, S Aarabi, P Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada

ISBN: (纸本)0819449598

A general method for time delay of arrival (TDOA) estimation for time-frequency information fusion is analyzed. This technique, for which the generalized cross correlation method and histogram methods are special cases, results in a low TDOA estimation error And high efficiency in computation. The proposed method relies on a non-linear phase-error selector function, which acts as a reward and punish method for the phase error at each frequency. Three different selector function candidates, consisting of cosine, rectangular, and triangular functions are analyzed using simulations. In the presence of Gaussian noise, the rectangular selector function performs better than the cosine at signal-to-noise ratios (SNRs) higher than 10dB while for lower SNRs the cosine function performs better. With speech noise, the cosine function, which corresponds to the generalized cross correlation technique, has higher anomaly percentages and higher root-mean-square errors than the rectangular function. This suggests, that in general, the rectangular selector function, which can be computed more easily than the cosine selector function, is superior technique to the generalized cross correlation method for. real-time applications.

关键词： delay-of-arrival estimation time-frequency data fusion microphone arrays speech processing

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Classification of terrain using multi-resolution satellite/aerial imagery and LiDAR data

Classification of terrain using multi-resolution satellite/a...

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Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2010

作者： Kocher, Brian R. Thomas, Alan M. Georgia Inst Technol Georgia Tech Res Inst Atlanta GA 30332 USA

ISBN: (纸本)9780819481740

High resolution LiDAR data is used to augment spectral data to improve resolution/accuracy. Digital elevation information, texture information, and spectral data are all combined into a single dataset and different clustering algorithms are used on the raster information and compared with clusters of spectral data alone. Long term goals of the work are to find efficient and effective methods of combining different data sets of varying resolution from different sources into a single dataset for analysis to improve data and classification resolution and accuracy.

关键词： image fusion image processing texture multispectral imagery lidar data material classification

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Generalized information fusion and Visualization Using Spatial Voting and Data Modeling

Generalized Information Fusion and Visualization Using Spati...

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Conference on multisensor. multisource information fusion - architectures, algorithms, and applications

作者： Jaenisch, Holger M. Handley, James W. SPIE Bellingham WA 98227 USA Licht Strahl Engn INC Toney AL 35773 USA Johns Hopkins Univ Baltimore MD 21218 USA

ISBN: (纸本)9780819495471

We present a novel and innovative information fusion and visualization framework for multi-source intelligence (multiINT) data using Spatial Voting (SV) and Data Modeling. We describe how different sources of information can be converted into numerical form for further processing downstream, followed by a short description of how this information can be fused using the SV grid. As an illustrative example, we show the modeling of cyberspace as cyber layers for the purpose of tracking cyber personas. Finally we describe a path ahead for creating interactive agile networks through defender customized Cyber-cubes for network configuration and attack visualization.

关键词： Spatial Voting Data Modeling information fusion Agile networks Cyber defense Cyber Persona Tracking

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A performance metric for belief fusion techniques

A performance metric for belief fusion techniques

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Conference on multisensor. multisource information fusion

作者： Friesel, MA Lockheed Martin Maritime Syst & Sensors Command & Control Syst Engn Moorestown NJ 08057 USA

ISBN: (纸本)0819457981

In this paper it is illustrated how Bayes equations and frequency data may use as a measure of performance for belief fusion algorithms. A review of Bayes equations for single and multiple sources is provided. A simple performance measure is then calculated and applied to some belief fusion examples from the literature. Their performance measures are qualitatively similar, but the quantitative differences among these techniques appear to be arbitrary.

关键词： belief theory datafusion performance characterization Bayes Dempster-Shafer combat identification

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Minimizing both dropped formulas and concepts in knowledge fusion

Minimizing both dropped formulas and concepts in knowledge f...

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Conference on multisensor. multisource information fusion

作者： Gregoire, Eric Univ Artois CRIL CNRS F-62307 Lens France

ISBN: (纸本)0819462985

In this paper, a new family of approaches to fuse inconsistent knowledge sources is introduced in a standard logical setting. They combine two preference criteria to arbitrate between conflicting information: the minimization of falsified formulas and the minimization of the number of the different atoms that are involved in those formulas. Although these criteria exhibit a syntactical flavor, the approaches are semantically-defined.

关键词： logic-based fusion knowledge fusion syntactical fusion operators

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Cognitive engineering in algorithm development for multisensor.data fusion in military applications

Cognitive engineering in algorithm development for multisens...

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Conference on multisensor. multisource information fusion

作者： Kight, AC Narayanan, S Wright State Univ Dept Biomed Ind & Human Factors Engn Dayton OH 45435 USA

ISBN: (纸本)0819453579

In battlefield situations, human operators are bombarded with substantial amounts of information and expected to make near-instantaneous decisions. The large amounts of information, coupled with short decision times and the need to reduce the potential of making incorrect decisions, create the possibility for information overload. This problem is especially prominent in military applications involving imagery from multiple sensors. Computer-based algorithms for fusing pertinent sets of imagery have proven somewhat useful for alleviating this problem. However, little research has been done on designing multisensor.data fusion systems using principles of cognitive engineering, which involves the consideration of human cognition during the design process. The design of a sensor fusion system using principles from cognitive engineering would create a more natural relationship between human and machine, and would thus be extremely effective in reducing operator error in military situations. This paper explores the need for integrating human reasoning and cognition in algorithm development for multisensor.fusion applications.

关键词： Algorithm development Data fusion Defense technologies Cognition Image fusion Error analysis Image sensors Sensor fusion Sensors

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Data fusion in road traffic engineering: An overview

Data fusion in road traffic engineering: An overview

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Conference on multisensor. multisource information fusion

作者： El Faouzi, NE ENTPE INRETS Transport & Traff Engn Lab F-69675 Bron France

ISBN: (纸本)0819453579

The objective of this paper is to present an analysis of recent applications of data fusion (DF) in road traffic engineering. First, we report the most significant applications of data fusion techniques in road traffic engineering area: traffic monitoring, signal control, Automatic Incident Detection, traffic forecasting, Intelligent Transportation Systems..., as well as the extent and direction of DF interest it the field. Second, a classification including applications, fusion goals and mathematical tools is proposed.

关键词： traffic engineering data fusion ITS theory of evidence Lalman filtering estimation fusion

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Optimal interval estimation fusion based on sensor interval estimates and confidence degrees

Optimal interval estimation fusion based on sensor interval ...

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Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2003

作者： Zhu, YM Li, BH Sichuan Univ Dept Math Chengdu 610064 Peoples R China

ISBN: (纸本)0819449598

The interval estimation fusion method based on sensor interval estimates and their confidence degrees is developed. When sensor estimates are independent of each other, a combination rule to merge sensor estimates and their confidence degrees is proposed. Moreover, two popular optimization-criteria: minimizing interval length with an allowable minimum confidence degree, or maximizing confidence degree with an allowable maximum interval length are suggested. In terms of the two criteria, an optimal interval estimation fusion can be obtained based on the combined intervals and their confidence degrees. Then we can extend the results on the combined interval outputs and. their confidence degrees to obtain a conditional combination rule and the corresponding optimal fault-tolerant interval estimation fusion in terms of the-two criteria. It is easy to see that Marzullo's fault-tolerant interval estimation fusion(11) is a special case of our method. We also point out that in some sense, our combination rule is similar to the combination rule in Dempster-Shafer evidence theory. However, the confidence degrees given in this paper is summable, but they (called mass function in Dempster-Shafer evidence theory) are not there;therefore, Dempster-Shafer's combination rule is not applicable to the interval estimation fusion.

关键词： interval estimation confidence degree combination ride optimal interval estimation fusion

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Multiple algorithm fusion in a corrosion detection algorithm used with shipboard tank and void inspection systems

Multiple algorithm fusion in a corrosion detection algorithm...

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Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2003

作者： Nelson, BN Slebodnick, P Lemieux, EJ CEO CENTERS Inc Newton Ctr MA 02459 USA

ISBN: (纸本)0819449598

Over the last several years the Naval Research Laboratory has developed video based systems for inspecting tanks (ballast, potable water, fuel, etc.) and other voids on ships. Over this past year, we have extensively utilized the Insertable Stalk Inspection System (ISIS) to perform inspections of shipboard tanks and voids. This system-collects between 15 and 30 images of the tank or void being inspected as well as a video archive of the complete inspection process. A corrosion detection algorithm analyzes the collected imagery. The corrosion detection algorithm output is the percent coatings damage in the tank being inspected. The corrosion detection algorithm consists of four independent algorithms that each separately assesses the coatings damage in each of the images that are analyzed. The algorithm results are fused to attain a single coatings damage value for each of the analyzed images. The damage values for each of the images are next aggregated in order to develop a single coatings damage value for the tank being inspected. This paper concentrates on the methods used to fuse the results from the four independent algorithms that assess corrosion damage at the individual image level as well as the methods used to aggregate the results from multiple images to attain a single coatings damage level. Results from both calibration tests and double blind testing are provided in the paper to demonstrate the advantages of the video inspection systems and the corrosion detection algorithm.

关键词： information fusion image processing automatic corrosion detection

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