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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181-190 订阅

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Classifiers and distance-based evidential fusion for road travel time estimation

Classifiers and distance-based evidential fusion for road tr...

引用

Conference on multisensor. multisource information fusion

作者： El Faouzi, N. -E. Lefevre, E. ENTPE INRETS Lab Ingn Circulat Transport 25 Ave Francois Mitterand Case 24 F-69675 Bron France Univ Artois Fac Sci Appl Lab Informat & Automat Artois LGI2A EA 3926 F-62400 Bethune France

ISBN: (纸本)0819462985

This paper addresses the road travel time estimation on an urban axis by classification method based on evidence theory. The travel time (IT) indicator can be used either for traffic management or for drivers' information. The information used to estimate the travel time (induction loop sensor, cameras, probe vehicle,...) is complementary and redundant. It is then necessary to implement strategies of multi-sensors data fusion. The selected framework is the evidence theory. This theory takes more into account the imprecision and uncertainty of multisource information. Two strategies were implemented. The first one is classifier fusion where each information source, was considered as a classifier. The second approach is a distance-based classification for belief functions modelling. Results of these approaches, on data collected on an urban axis in the South of France, show the outperformance of fusion strategies within this application.

关键词： evidence theory classifier combination travel time estimation

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The contourlet transform for image fusion

The contourlet transform for image fusion

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Conference on multisensor. multisource information fusion

作者： Miao Qiguang Wang Baoshu Xidian Univ Sch Comp Sci Xian 710071 Peoples R China Guilin Univ Elect Technol Guilin 541004 Peoples R China

ISBN: (纸本)0819462985

In this paper, we introduce a new image fusion method based on the contourlet transform. Firstly, the problem that wavelet transform could not efficiently represent the singularity of linear/curve in image processing is analyzed. Secondly, the principal of Contourlet and its good performance in expressing the singularity of two or higher dimensional are studied. Finally, the feasibility of image fusion using contourlet transform is discussed in detail. A new fusion method based on Contourlet transform and the fusion framework are proposed. The transform coefficients structure and the fusion procedure are given in detail in this paper. Experiments show that the proposed algorithm works better in preserving the edge and texture information than the wavelet transform method and the Laplacian pyramid methods do in image fusion.

关键词： image fusion contourlet transform pyramidal directional filter bank singularity

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The challenge of scalable and distributed fusion of disparate sources of information

The challenge of scalable and distributed fusion of disparat...

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Conference on multisensor. multisource information fusion

作者： Julier, Simon J. Uhlmann, Jeffrey K. Walters, Joshua Mittu, Ranjeev Palaniappan, Kannappan ITT AES NRL 4555 Overlook Ave Washington DC 20375 USA Univ Missouri Dept Comp Sci Columbia MO 65211 USA Naval Res Lab Washington DC 20375 USA

ISBN: (纸本)0819462985

A key enabler for Network Centric Warfare (NCW) is a sensor network that can collect and fuse vast amounts of disparate and complementary information from sensors that are geographically dispersed throughout the battlespace. This information will lead to better situation awareness so that commanders will be able to act faster and more effectively. However, these benefits are possible only if the sensor data can be fused and synthesized for distribution to the right user in the right form at the right time within the constraints of available bandwidth. In this paper we consider the problem of developing Level 1 data fusion algorithms for disparate fusion in NCW. These algorithms must be capable of operating in a fully distributed (or decentralized) manner;must be able to scale to extremely large numbers of entities;and must be able to combine many disparate types of data. To meet these needs we propose a framework that consists of three main components: an attribute-based state representation that treats an entity state as a collection of attributes, new methods or interpretations of uncertainty, and robust algorithms for distributed data fusion. We illustrate the discussion in the context of maritime domain awareness, mobile adhoc networks, and multispectral image fusion.

关键词： distributed data fusion disparate data fusion generalized Covariance Intersection correlated data MANET maritime domain awareness

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Realizing Situation Awareness in a cyber environment

Realizing Situation Awareness in a cyber environment

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Conference on multisensor. multisource information fusion

作者： Tadda, George Salerno, John J. Boulware, Douglas Hinman, Michael Gorton, Samuel USAF Res Lab 525 Brooks Rd Rome NY 13441 USA Skaion Corp North Chelmsford MA 01863 USA

ISBN: (纸本)0819462985

Situation Awareness (SA) problems all require an understanding of current activities, an ability to anticipate what may happen next, and techniques to analyze the threat or impact of current activities and predictions. These processes of SA are common regardless of the domain and can be applied to the detection of cyber attacks. This paper will describe the application of a SA framework to implementing Cyber SA, describe some metrics for measuring and evaluating systems implementing Cyber SA, and discuss ongoing work in this area. We conclude with some ideas for future activities.

关键词： advanced fusion situation awareness Cyber Situation Awareness

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MeRIS and ETM image fusion for spatial resolution improvement

MeRIS and ETM image fusion for spatial resolution improvemen...

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Conference on multisensor. multisource information fusion

作者： Minghelli-Roman, Audrey Mathieu, Sandrine Polidori, Laurent Loubersac, Lionel Cauneau, Francois Univ Bourgogne CNRS UMR 5158 LE21 F-21078 Dijon France Alcatel Alenia Space Ind F-06156 Cannes France IRD Lab Reg Teledetect Cayenne 97323 French Guiana IFREMER DEL DRV LER LR F-34203 Sete France Ecole Mines Paris Ctr Energetique Grp T&M F-06904 Sophia Antipolis France

ISBN: (纸本)0819462985

MeRIS was launched in March 2002 and has been providing images since June 2002. Before its launch, we had implemented a method to improve its resolution by merging its images with Landsat ETM images in order to preserve the best characteristics of the two images (spatial, spectral, temporal). We now present the results of this method for real MeRIS images (level 1b and 2) in a coastal area. The robustness of the method is studied as well as the influence of the delay between the acquisitions of the two images

关键词： fusion ETM MeRIS

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Feature selection for real-time tracking

Feature selection for real-time tracking

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Conference on multisensor. multisource information fusion

作者： Hsu, D. Frank Lyons, Damian M. Ai, Jizhou Fordham Univ Dept Comp & Informat Sci Robot & Comp Vis Lab Bronx NY 10458 USA

ISBN: (纸本)0819462985

We address the problem of selecting features to improve automated video tracking of targets that undergo multiple mutual occlusions. As targets are occluded, different feature subsets and combinations of those features are effective in identifying the target and improving tracking performance. We use Combinatorial fusion Analysis to develop a metric to dynamically select which subset of features will produce the most accurate tracking. In particular we show that the combination of a pair of features A and B will improve the accuracy only if (a) A and B have relative high performance, and (b) A and B are diverse. We present experimental results to illustrate the performance of the proposed metric.

关键词： video surveillance target tracking feature selection sensory fusion

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Higher-level fusion for military operations based on abductive inference: Proof of principle

Higher-level fusion for military operations based on abducti...

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Conference on multisensor. multisource information fusion

作者： Pantaleev, Aleksandar Josephson, John Ohio State Univ Lab Artificial Intelligence Res 2015 Neil Ave Columbus OH 43210 USA

ISBN: (纸本)0819462985

The ability of contemporary military commanders to estimate and understand complicated situations already suffers from information overload, and the situation can only grow worse. We describe a prototype application that uses abductive inferencing to fuse information from multiple sensors to evaluate the evidence for higher-level hypotheses that are close to the levels of abstraction needed for decision making (approximately JDL levels 2 and 3). Abductive inference (abduction, inference to the best explanation) is a pattern of reasoning that occurs naturally in diverse settings such as medical diagnosis, criminal investigations, scientific theory formation, and military intelligence analysis. Because abduction is part of common-sense reasoning, implementations of it can produce reasoning traces that are very human understandable. Automated abductive inferencing can be deployed to augment human reasoning, taking advantage of computation to process large amounts of information, and to bypass limits to human attention and short-term memory. We illustrate the workings of the prototype system by describing an example of its use for small-unit military operations in an urban setting. Knowledge was encoded as it might be captured prior to engagement from a standard military decision making process (MDMP) and analysis of commander's priority intelligence requirements (PIR). The system is able to reasonably estimate the evidence for higher-level hypotheses based on information from multiple sensors. Its inference processes can be examined closely to verify correctness. Decision makers can override conclusions at any level and changes will propagate appropriately.

关键词： abduction abductive inference best-explanation reasoning multisource information fusion multisensor.fusion higher-level fusion priority intelligence requirements PIR JDL level 2 JDL level 3

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Fusing diverse monitoring algorithms for robust change detection

Fusing diverse monitoring algorithms for robust change detec...

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Conference on multisensor. multisource information fusion

作者： Goebel, Kai F. Hu, Xiao Eklund, Neil H. W. Yan, Weizhong GE Global Res 1 Res Circle Niskayuna NY 12309 USA

ISBN: (纸本)0819462985

Change detection is an important task in remotely monitoring and diagnosing equipment and other processes. Specifically, early detection of differences that indicate abnormal conditions has the promise to provide considerable savings in averting secondary damage and preventing system outage. Of course, accurate early detection has to be balanced against the successful rejection of false positive alarms. In noisy environments, such as aircraft engine monitoring, this proves to be a difficult undertaking for any one algorithm. In this paper, we investigate the performance improvement that can be gained by aggregating the information from a set of diverse change detection algorithms. Specifically, we examine a set of change detectors that utilize a variety of different techniques such as neural nets, random forests, and support vector machines. The different techniques have different detection sensitivities and different false positive rates. For fusion, we consider the Dempster regression technique that operates well for time series as well as averaging schemes, and a meta-classifiers. We provide results using illustrative examples from aircraft engine monitoring.

关键词： change detection diagnostics abnormal condition detection information fusion classifier fusion

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Multi-source evidence fusion for cyber-situation assessment

Multi-source evidence fusion for cyber-situation assessment

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Conference on multisensor. multisource information fusion

作者： Sabata, Bikash Ornes, Chester Aginova Inc 7901 Henry AveB-109 Philadelphia PA 19128 USA Informat Extract & Transport Inc Arlington VA 22209 USA

ISBN: (纸本)0819462985

Novel methods of detecting cyber attacks on networks have been developed that are able to detect an increasing diverse variety of malicious cyber-events. However, this has only resulted in additional information burden on the network analyst. The integration of the distributed evidence from multiple sources is missing or ad-hoc at best. Only with the fusion of the multi-source evidence can we reason at a higher semantic level to detect and identify attacks and attackers. Further, integration at a higher semantic level will reduce the cognitive load on the security officer and will make it possible for reasonable responses. This paper presents an overview of the D-Force system that uses a Bayesian Evidential Framework for fusing the multi-source evidence in a network to detect and recognize attacks. Attack hypothesis are generated as a result of evidence at the different network and host sensors. The hypotheses are verified or denied with additional evidence. Based on our initial experiments and tests the D-Force system promises to be a powerful tool in the information security officers arsenal.

关键词： cyber situation assessment intrusion detection cyber attacks

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Measuring Situational Awareness and resolving inherent high-level fusion obstacles

Measuring Situational Awareness and resolving inherent high-...

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Conference on multisensor. multisource information fusion

作者： Sudit, Moises Stotz, Adam Holender, Michael Tagliaferri, William Canarelli, Kathie SUNY Coll Buffalo Ctr Multisource Informat Fus Buffalo NY 14062 USA CUBRC Buffalo NY 14221 USA Alion Sci & Technol Rome 13440 NY USA

ISBN: (纸本)0819462985

information fusion Engine for Real-time Decision Making (INFERD) is a tool that was developed to supplement current graph matching techniques in information fusion models. Based on sensory data and a priori models, INFERD dynamically generates, evolves, and evaluates hypothesis on the current state of the environment. The a priori models developed are hierarchical in nature lending them to a multi-level information fusion process whose primary output provides a situational awareness of the environment of interest in the context of the models running. In this paper we look at INFERD's multi-level fusion approach and provide insight on the inherent problems such as fragmentation in the approach and the research being undertaken to mitigate those deficiencies. Due to the large variance of data in disparate environments, the awareness of situations in those environments can be drastically different. To accommodate this, the INFERD framework provides support for plug-and-play fusion modules which can be developed specifically for domains of interest. However, because the models running in INFERD are graph based, some default measurements can be provided and will be discussed in the paper. Among these are a Depth measurement to determine how much danger is presented by the action taking place, a Breadth measurement to gain information regarding the scale of an attack that is currently happening, and finally a Reliability measure to tell the user the credibility of a particular hypothesis. All of these results will be demonstrated in the Cyber domain where recent research has shown to be an area that is well-defined and bounded, so that new models and algorithms can be developed and evaluated.

关键词： graphs defragmentation real-time decision-making Situational Awareness

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