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检索条件"任意字段=Conference on Sensor Fusion: Architectures, Algorithms, and Applications IV"

共 329 条记录，以下是31-40 订阅

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Proceedings of SPIE: sensor fusion: architectures, algorithms, and applications II

Proceedings of SPIE: Sensor Fusion: Architectures, Algorithm...

引用

sensor fusion: architectures, algorithms and applications II

This Volume 3376 of the conference proceedings contains 22 papers. Topics discussed include sensor fusion, sensor fusion architectures, feature and decision level fusion, data and image level fusion and sensor fusion ... 详细信息

关键词： sensor data fusion

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The principle for synthesizing measurements of multiple system parameters into a single parameter

The principle for synthesizing measurements of multiple syst...

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conference on sensor fusion - architectures, algorithms, and applications VI

作者： Pu, QG Univ Sci & Technol Suzhou Ctr Comp Suzhou 215011 Jiangsu Peoples R China

ISBN: (纸本)0819444812

Modern technology provides a great amount of information. In computer monitoring systems or computer control systems, especially real-time expert systems, in order to have the situation in hand, we need one or two parameters to express the quality and/or security of the whole system. This paper presents a principle for synthesizing measurements of multiple system parameters into a single parameter. This principle has been successfully applied in the monitoring of an ultra-energy efficient house in Canada and other applications.

关键词： sensor fusion parameter synthesis computer monitoring systems computer control systems real -time expert systems

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The equivalence of Bayesian multi-sensor information fusion and neural networks

The equivalence of Bayesian multi-sensor information fusion ...

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conference on sensor fusion - architectures, algorithms, and applications V

作者： Aarabi, P Stanford Univ Dept Comp Sci Stanford CA 94305 USA

ISBN: (纸本)0819440809

This paper proposes a Bayesian multi-sensor object localization approach that keeps track of the observability of the sensors in order to maximize the accuracy of the final decision. This is accomplished by adaptively monitoring the mean-square-error of the results of the localization system. Knowledge of this error and the distribution of the system's object localization estimates allow the result of each sensor to be scaled and combined in an optimal Bayesian sense. It is shown that under conditions of normality, the Bayesian sensor fusion approach is directly equivalent to a single layer neural network with a sigmoidal non-linearity. Furthermore, spatial and temporal feedback in the neural networks can be used to compensate for practical difficulties such as the spatial dependencies of adjacent positions. Experimental results using 10 binary microphone arrays yield an order of magnitude improvement in localization error for the proposed approach when compared to previous techniques.

关键词： object localization sensor fusion neural networks sound localization

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Data level fusion using common symmetry set

Data level fusion using common symmetry set

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conference on sensor fusion - architectures, algorithms, and applications III

作者： Tari, S Middle E Tech Univ Dept Engn Sci TR-06531 Ankara Turkey

ISBN: (纸本)0819431931

Availability of different imaging modalities requires techniques to process and combine information from different images of the same phenomena. We present a symmetry based approach for combining information from multiple images. fusion is performed at data level. Actual object boundaries and shape descriptors are recovered directly from raw sensor output(s). Method is applicable to arbitrary number of images in arbitrary dimension.

关键词： Image fusion Data fusion Image segmentation sensors Image processing Information fusion Data processing Shape analysis 3D image processing Image analysis

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Pattern-level temporal difference learning, data fusion, and chess

Pattern-level temporal difference learning, data fusion, and...

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conference on sensor fusion: architectures, algorithms, and applications iv

作者： Levinson, R Weber, R Univ Calif Santa Cruz Santa Cruz CA 95064 USA

ISBN: (纸本)0819436771

Our research group is using chess as a vehicle for studying the fusion of adaptation, multiple representation, and search technologies for real-time decision making. Chess systems like Deep Blue have achieved Grandmaster chess play with a brute-force search of the game tree and human-supplied information, like piece-values and opening books. However, subtle aspects of chess, including positional features and advanced concepts, are not capable of being represented or processed efficiently with the standard method. Since 1989, Morph I-III have exhibited more autonomy and learning ability than traditional chess programs in "adaptive pattern-oriented chess". (2) Like its predecessors, Morph TV is a reinforcement learner, but it also uses a new technique we call pattern-level TD and Q-learning to mathematically map the state space and effectively learn to classify situations. Its three knowledge sources include two traditional ones: material and a piece-square table, and a new method called Distance. These are combined using a simple genetic algorithm and a decision tree. This paper shows the effectiveness of fusing knowledge to replace search in real-time situations, since an agent which combines all sources is capable of consistently beating an agent which employs any of the individual knowledge sources. Surprisingly, the pattern-level TD agent is slightly superior to the pattern-level Q-learning agent, despite the fact that the Q-learning agent updates more Q-values on each temporal step.

关键词： Q-learning temporal difference decision trees genetic algorithms chess search distance pattern oriented knowledge acquisition

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sensor fusion cognition using belief filtering for tracking and identification

Sensor fusion cognition using belief filtering for tracking ...

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conference on sensor fusion - architectures, algorithms, and applications III

作者： Blasch, E Hong, L SNAT AFRL Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819431931

Humans exhibit remarkable abilities to estimate, filter, predict, and fuse information in target tracking tasks. To improve track quality, we extend previous tracking approaches by investigating human cognitive-level fusion for constraining the set of plausible targets where the number of targets is not known a priori. The target track algorithm predicts a belief in the position and pose for a set of targets and an automatic target recognition algorithm uses the pose estimate to calculate an accumulated target-belief classification confidence measure. The human integrates the target track information and classification confidence measures to determine the number and identification of targets. This paper implements the cognitive belief filtering approach for sensor fusion and resolves target identify through a set-theory approach by determining a plausible set of targets being tracked.

关键词： sensor fusion target recognition classification & identification tracking cognitive belief filter HRR

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Identity and attribute information fusion using evidential reasoning

Identity and attribute information fusion using evidential r...

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conference on sensor fusion - architectures, algorithms, and applications

作者： Bosse, E Simard, MA Defence Research Establishment Valcartier (Canada) Lockheed Martin Canada (Canada)

ISBN: (纸本)081942482X

The aim of this paper is to explore the problem of fusing identity and attribute information emanating from different sources, and to offer the decision maker a quantitative analysis based on statistical methodology that can enhance his/her decision making process regarding the identity of detected objects. Two identity information fusion architectures are discussed here. The first is concerned with the fusion of identity declarations where the sources are expected to provide only useful and complete results such as an identity declaration. The second is concerned with the fusion of attribute information using a modified version of the Dempster-Shafer evidential combination algorithm.

关键词： sensors Information fusion Data fusion Data processing Radar Electronic support measures Telecommunications Signal processing Databases Probability theory

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Registration of scenes for the detection of concealed weapons

Registration of scenes for the detection of concealed weapon...

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conference on sensor fusion - architectures, algorithms, and applications III

作者： Slamani, MA Varshney, PK Alford, MG Ferris, D Stiefvater Consultants Inc Marcy NY 13403 USA

ISBN: (纸本)0819431931

A number of sensors are being developed for the Concealed Weapon Detection (CWD), and use of the appropriate sensor or combination of sensors will be: very important to the success of such technologies. Assuming that two identical sensors are used to collect data on a target from different angular views, this paper addresses the problem of registration associated with the collected scenes. Theory and application to real data are presented.

关键词： image registration Concealed Weapons Detection A'SCAPE enhancement fusion

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Information fusion benefits delineation in off-nominal scenarios

Information fusion benefits delineation in off-nominal scena...

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conference on sensor fusion - architectures, algorithms, and applications III

作者： Dasarathy, BV Dynet Inc Huntsville AL 35814 USA

ISBN: (纸本)0819431931

The potential problem of deterioration In recognition system performance because of imprecise, incomplete, or imperfect training is a serious challenge inherent to most real-world applications. This problem is often referred to in certain applications as degradation of performance under off-nominal conditions. This study presents the results of an investigation carried out to illustrate the scope and benefits of information fusion in such off-nominal scenarios. The research covers features in - decision out (FEI-DEO) fusion as well as decisions in - decision out (DEI-DEO) fusion. The latter spans across both information sources (sensors) and multiple processing tools (classifiers). The investigation delineates the corresponding fusion benefit domains using as an example, real-world data from an audio-visual system for the recognition of French oral vowels embedded in various levels of acoustical noise.

关键词： information fusion off-nominal scenarios audio-visual fusion vowel recognition

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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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