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检索条件"任意字段=Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012"

共 282 条记录，以下是251-260 订阅

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Design of a performance evaluation methodology for data fusion-based multiple target tracking systems

Design of a performance evaluation methodology for data fusi...

引用

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

作者： Rawat, S Llinas, J Bowman, C SUNY Buffalo Ctr Multisource Informat Fus Buffalo NY 14260 USA

ISBN: (纸本)0819449598

The emphasis of this paper is to design a Performance Evaluation Methodology for Data fusion-based Multiple Target Tracking Systems. Within this methodology the Performance Evaluation process is treated as a whole new fusion process. This has two major advantages - (1) Facilitates reusability of existing models and algorithms, and (2) Using standard frameworks and norms makes it easier for the tracking community to easily adopt it - thus giving this aspect of tracking a highly needed jumpstart. A case study implementation of this design methodology is presented. Three different Track-Truth Association strategies were implemented to study the effect of Track-Truth Association strategies on the performance metrics. The case study results conclusively show that the selection of the Track-Truth Association strategy should be done with reference to the scenario characteristics, the "mission" goals and the performance metrics to be evaluated.

关键词： data fusion target tracking performance evaluation

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Fusing multiple images with evidential reasoning

Fusing multiple images with evidential reasoning

引用

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

作者： Yuan, XH Jian, Z Buckles, BP Tulane Univ Dept Elect Engn & Comp Sci New Orleans LA 70001 USA

ISBN: (纸本)0819449598

An approach to fuse multiple images based on Dempster-Shafer evidential reasoning is proposed in this, article. Dempster-Shafer theory provides a complete framework for combining weak evidences from multiple sources. Such situations typically arise in the image fusion problems, where a 'real scene' image has to be estimated from incomplete and unreliable observations. By converting images from their spatial domain into the evidential representations, decisions are made to aggregate evidences such that a fused image is generated. The proposed fusion approach is evaluated on a broad set of images and promising results are given.

关键词： image fusion evidential reasoning multiscale decomposition

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A simple test-bed for real-time sensor-to-shooter applications of decentralised data fusion

A simple test-bed for real-time sensor-to-shooter applicatio...

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

作者： Binns, L Cooke, A Fryers, S Greenway, P Mullin, D Nicholson, D Valachis, D BAE Syst Adv Technol Ctr Bristol BS34 7QW Avon England

ISBN: (纸本)0819449598

In this paper we describe a simple physical test-bed, developed to allow practical experimentation in the use of Decentralised Data fusion (DDF) in sensor-to-shooter applications. Running DDF over an ad hoc network of distributed sensors produces target location information. This is used to guide a Leica laser-tracker system to designate currently tracked targets. We outline how the system is robust to network and/or node failure. Moreover, we discuss the system properties that lead to it being completely "plug-and-play", as, like the distributed sensor nodes, the "shooter" does not require knowledge of the overall network topology and can connect at any point.

关键词： data fusion network centric warfare ad-hoc networks sensor-to-shooter

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A neurophysiological paradigm for data fusion in a multisource environment

A neurophysiological paradigm for data fusion in a multisour...

引用

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

作者： Fisher, PS Minton, DH Fisher, HP Winston Salem State Univ Dept Comp Sci Winston Salem NC 27110 USA

ISBN: (纸本)0819449598

A technique for representing data obtained from sensors, video streams. imagery, sound, text, etc. is presented. The technique is called Finite Inductive Sequences (FI) and is proposed as a means for eliminating data requiring storage where conventional mathematical models don't eliminate enough and statistical models eliminate too much. FI is a simple idea and is based upon a symbol push-out technique that allows the order (inductive base) of the model to be set to an a priori value for all derived rules. The rules are obtained from an exemplar data set, and are derived by a technique called factoring, and this results in a table of rules called a ruling. These rules can then be used in pattern recognition applications. These techniques are shown be example as well as a more formal setting, and lastly these rules and ruling are likened to the structure both present and absent in the cerebellum.

关键词： pattern recognition cerebellum data models finite induction data storage finite induction

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Discrimination of Chemical/Biological versus high explosive artillery rounds using acoustic and seismic data fusion

Discrimination of Chemical/Biological versus high explosive ...

引用

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

作者： Reiff, C Fargues, M Gonski, D US Army Res Lab Adelphi MD 20783 USA

ISBN: (纸本)0819449598

The threat of chemical and biological weapons is a serious problem and the ability to determine. if an incoming artillery round contains high explosives or a chemical/biological agent is valuable information to anyone on the battlefield. Early detection of a chemical or biological agent provides the soldier with more time to respond to the threat. information about the round type and location can be obtained from acoustic and seismic sensors and fused with information from radars, infrared and video cameras, and meteorological sensors to identify the round type quickly after detonation. This paper will describe the work with ground based acoustic and seismic sensors to discriminate between round types in a program sponsored-by the Soldier Biological and Chemical Command.

关键词： chemical biological artillery discrimination data fusion acoustic seismic

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Multi-level image fusion

Multi-level image fusion

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

作者： Petrovic, V Orasys MV YU-11077 Novi Beograd Serbia Yugoslavia

ISBN: (纸本)0819449598

Signal-level image fusion has in recent years established itself as a useful tool for dealing with vast amounts of image data obtained by disparate sensors. In many modem multisensor systems, fusion algorithms significantly reduce the amount of raw data that needs to be presented or processed without loss of information content as well as provide an effective way of information integration. One of the most useful and widespread applications of signal-level image fusion is for display purposes. Fused images provide the observer with a more reliable and more complete representation of the scene than would be obtained through single sensor display configurations. In recent years, a plethora of algorithms that deal with the problem of fusion for display has been proposed. However, almost all are based on relatively basic processing techniques and do not consider information from higher levels of abstraction. As some recent studies have shown this does not always satisfy the complex demands of a human observer and a more subjectively meaningful approach is required. This paper presents a fusion framework based on the idea that subjectively relevant fusion could be achieved if information at higher levels of abstraction such as image edges and image segment boundaries are used to guide the basic signal-level fusion process. fusion of processed, higher level information to form a blueprint for fusion at signal level and fusion of information from multiple levels of extraction into a single fusion engine are both considered. When tested on two conventional signal-level fusion methodologies, such multi-level fusion structures eliminated undesirable effects such as fusion artefacts and loss of visually vital information that compromise their usefulness. Images produced by inclusion of multi-level information in the fusion process are clearer and of generally better quality than those obtained through conventional low-level fusion. This is verified through subjective evaluatio

关键词： image fusion signal-level fusion feature-level fusion multi-level fusion

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multisensor data fusion technologies in counterchecking disturbed targets

Multisensor data fusion technologies in counterchecking dist...

引用

multisensor. multisource information fusion: architectures, algorithms, and applications 2003

作者： Wang, Ju Wu, Siliang Dept. of Electronics Engineering Beijing Institute of Technology Beijing 100081 China

The technique of data fusion is a new kind of data processing technique and has broad appliance foreground. Appearance of stealthy and disturbed targets in modern battlefield leads to data extraction and fusion by networking various sensors to maximize use of information to perform recognition, orientation and tracking of targets. As we known well, radar only acquire angle information without range information when encounter noise suppress jammer. Netted radars could get position information of interference by make use of radars position relatively and target angle information. Yet if there is more than one target, the orientation of targets could error due to orientation confuse. The paper present methods that through association arithmetic of kalman filter to avoid confuse.

关键词： Sensor data fusion

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Sensitivity of fusion performance to classifier model variations

Sensitivity of fusion performance to classifier model variat...

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

作者： Goebel, K GE Global Res Niskayuna NY 12309 USA

ISBN: (纸本)0819449598

During design of classifier fusion tools, it is important to evaluate the performance of the fuser. In many cases, the output of the classifiers needs to be simulated to provide the range of fusion input that allows an evaluation throughout the design space. One fundamental question is how the output should be distributed, in particular for multi-class continuous output classifiers. Using the wrong distribution may lead to fusion tools that are either overly optimistic or otherwise distort the outcome. Either case may lead to a fuser that performs sub-optimal in practice. It is therefore imperative to establish the bounds of different classifier output distributions. In addition, one must take into account the design space that may be of considerable complexity. Exhaustively simulating the entire design space may be a lengthy undertaking. Therefore, the simulation has to be guided to populate the relevant areas of the design space. Finally, it is crucial to quantify the performance throughout the design of the fuser. This paper addresses these issues by introducing a simulator that allows the evaluation of different classifier distributions in combination with a design of experiment setup, and a built-in performance evaluation. We show results from an application of diagnostic decision fusion on aircraft engines.

关键词： classification diagnostics information fusion decision fusion simulation

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Adaptive multimodal biometric fusion algorithm using particle swarm

Adaptive multimodal biometric fusion algorithm using particl...

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

作者： Veeramachaneni, K Osadciw, LA Varshney, PK Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

ISBN: (纸本)0819449598

This paper introduces a new algorithm called Adaptive Multimodal Biometric fusion Algorithm" (AMEBF), which is a combination of Bayesian decision fusion and particle swarm optimization. A Bayesian framework is implemented to fuse decisions received from multiple biometric sensors. The system's accuracy improves for a subset of decision fusion rules. The optimal rule is-a function of the error cost and a priori probability of an intruder This Bayesian framework formalizes the design of a system that can adoptively increase or reduce the security level. Particle swarm optimization searches the decision and sensor operating points (i.e. thresholds) space to achieve the desired security level: The optimization function aims to minimize the cost in a Bayesian decision fusion. The particle swarm optimization algorithm results in the fusion rule and the operating points of sensors at which the system can work This algorithm is important to systems designed with varying security needs and user access requirements. The adaptive algorithm is found to achieve desired security level and switch between different rules and sensor operating points for varying needs.

关键词： Bayesian decision fusion particle swarm optimization multimodal biometrics

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The application of Dempster-Shafer theory for landmine detection

The application of Dempster-Shafer theory for landmine detec...

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

作者： Mudigonda, NR Kacelenga, R Erickson, D Gen Dynam Canada Ltd Calgary AB T2E 8P2 Canada

ISBN: (纸本)0819449598

This paper explores the concepts of multisensor data fusion based on the Dempster-Shafer (DS) evidential theory in order to achieve a mine versus false-alarm (FA) classification of landmine targets. Initially, a decision-level DS algorithm is proposed to combine the evidence from multiple sensors of the landmine detection system developed by the General Dynamics Canada Limited (GD Canada). Subsequently, a feature-level DS fusion algorithm is employed to operate on a set of features reported by the ground penetrating radar (GPR) sensor of the system. The data used in the present study was acquired from the Aberdeen Proving Grounds (APG) test site in USA as part of the Ground Standoff Mine Detection System (GSTAMIDS) trials. The proposed decision-level DS algorithm yielded a probability of detection (Pd) of 92.53% at a false-alarm rate (FAR) value of 0.0697 FAs/m(2). The Pd and the FAR performance results achieved by using the decision-level DS algorithm are comparable with the results obtained using three other decision-level fusion algorithms that were previously developed by GD, Canada based on heuristic, Bayesian inference, and Voting fusion concepts. On the other hand, the feature-level DS fusion, when tested with the information presented by the GPR sensor only, resulted in a higher Pd value of 78.54% as compared to the corresponding result of 61.43% obtained by using the heuristic algorithm. The GPR sensor is one of the three scanning sensors present on the system.

关键词： landmine detection multisensor data fusion Dempster-Shafer theory Bayesian theory voting fusion

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