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检索条件"任意字段=Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2007"

共 282 条记录，以下是21-30 订阅

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information fusion of large number of sources with support vector machine techniques

Information fusion of large number of sources with support v...

引用

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

作者： Braun, JJ Jeswani, SP MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (纸本)0819449598

applications of information fusion include cases that involve a large number of information sources. Methods developed in the context of few information sources may not, and often do not, scale well to cases involving a large number of sources. This paper addresses specifically the problem of information fusion of large number of information sources. Performance of Support Vector Machine (SVM) based approach is investigated in input spaces consisting of thousands of information sources. Microarray pattern recognition, an important bioinformatics task with significant medical diagnostics applications, is considered from the information and sensor data fusion viewpoint, and recognition performance experiments conducted on microarray data are discussed. An approach involving high-dimensional input space partitioning is presented and its efficacy is investigated. The aspects of feature-level and decision-level fusion are discussed as well. The results indicate the feasibility of the SVM based information fusion with large number of information sources.

关键词： information fusion multisensor data fusion bioinformatics microarrays Support Vector Machine

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Multi-sensor fusion using an adaptive multi-hypothesis tracking algorithm

Multi-sensor fusion using an adaptive multi-hypothesis track...

引用

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

作者： Kester, LJHM TNO Phys & Elect Lab NL-2509 JG The Hague Netherlands

ISBN: (纸本)0819449598

The purpose of a tracking algorithm is to associate data measured by one or more (moving) sensors to moving objects in the environment. The state of these objects that can be estimated with the tracking process depends on the type of data that is provided by these sensors. It is discussed how the tracking algorithm can adapt itself, depending on the provided data, to improve data association. The core of the tracking algorithm,is an extended Kalman filter using multiple hypotheses for contact to track association. Examples of various sensor suites of radars, electro-optic sensors and acoustic sensors are presented.

关键词： sensor fusion tracking data association MHT

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The system parameter fusion principle and its application to fuzzy pattern recognition

The system parameter fusion principle and its application to...

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

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

ISBN: (纸本)0819449598

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 and its application to fuzzy pattern recognition.

关键词： sensor fusion fuzzy pattern recognition computer monitoring systems computer control systems realtime expert systems

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Non-algorithmic information fusion

Non-algorithmic information fusion

引用

Conference on multisensor, multisource information fusion

作者： Brander, Jim Interact Engn Sydney NSW Australia

ISBN: (纸本)9780819471659

This paper considers the applicability of algorithms, constraint solving and active structure across the spectrum of complexity of information fusion applications. information fusion is recast as a cognitive application using dynamic structure building and constraint reasoning. The similarity between situation awareness and an undirected structure responding to change is highlighted. The efficiency and speed of operation of cognitive information fusion are touched on. A tsunami warning system provides an example which involves multiple threat and demonstrates the difference between segmented algorithms making decisions without context, and the active use of knowledge.

关键词： non-algorithmic undirected constraint reasoning active structure self-modifiable dynamically extensible cognitive core

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Level 0-2 fusion model for ATR using fuzzy logic

<i>Level 0</i>-<i>2</i> fusion model for ATR using fuzzy log...

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

作者： Hester, Charles F. Dobson, Kelly K. U.S. Army Aviation and Missile Research Development and Engineering Ctr. United States

ISBN: (纸本)9780819481740

The JDL model for fusion provides a structure for fusion of multispectral data at all levels. Fused data provides improved performance in Automatic Target Recognition (ATR). Critical to the overall fusion performance, however, is the low level(0-2) fusion of sensory and context information. Loss of information must be avoided at this level, but complexity must be reduced. A model is presented that uses fuzzy sets to form entities and capture the information needed for target recognition. Examples using multi-spectral imagery will be presented.

关键词： fuzzy logic ATR level 0-2 fusion JDL model

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Novel classification fusion techniques for military target classification

Novel classification fusion techniques for military target c...

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Conference on multisensor, multisource information fusion

作者： Liu, Ting Lampropoulos, George A. AUG Signals 73 Richmond St W Toronto ON Canada

ISBN: (纸本)9780819466938

The objective of this paper is to develop novel classification structures for military targets detection and recognition by employing different fusion techniques. In real applications, the great diversity of materials in the background areas and the similarity between the background and target signatures result in high false alarm rates and large miss classification errors. In this paper, three new systems are proposed using different fusion techniques: pixel level fusion, decision fusion, and classification fusion employing confidence vectors. These new developed systems are tested using an experimental data to show its effectiveness.

关键词： hyperspectral detection classification fusion confusion matrix false alarm

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Uncertainty Characterization Using Copulas for Classification

Uncertainty Characterization Using Copulas for Classificatio...

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

作者： Ozdemir, Onur Choi, Sora Allen, Thomas G. Varshney, Pramod K. Boston Fus Corp Burlington MA 01824 USA Syracuse Univ Dept EECS Syracuse NY USA

ISBN: (纸本)9781628416145

We address the problem of characterizing uncertainty for multisensor data fusion in a classification problem. To achieve this goal, we model the joint density of given multivariate data using copula functions while allowing the ability to incorporate any desired marginal distributions, i.e., any desired modalities. The proposed model is data driven in that the corresponding copula functions and their parameters are learned from the data. Our results show that the proposed framework can capture the uncertainties more accurately than current state of the practice, and lead to robust and improved classification performance compared to traditional classifiers.

关键词： multisource data fusion copula theory classification

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multisource taxonomy-based classification using the transferable belief model

Multisource taxonomy-based classification using the transfer...

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

作者： Farrell, William J., III Knapp, Andrew M. Lakota Tech Solut Inc Laurel MD USA

ISBN: (纸本)9780819490858

This paper addresses the problem of multi-source object classification in a context where objects of interest are part of a known taxonomy and the classification sources report at varying levels of specificity. This problem must consider several technical challenges: a) support fusion of heterogeneous classification inputs, b) provide a computationally scalable approach that accommodates taxonomy's with thousands of leaf nodes, and c) provide outputs that support tactical decision aides and are suitable inputs for subsequent fusion processes. This paper presents an approach that employs the Transferable Belief Model, Pignistic Transforms, and Bayesian fusion to address these challenges.

关键词： Evidence Theory Transferable Belief Model Pignistic Transform Bayesian fusion information Theory Classification Data Association

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Distributed fault-tolerant classification fusion using error correcting codes

Distributed fault-tolerant classification fusion using error...

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

作者： Wang, TY Varshney, PK Han, YS Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

ISBN: (纸本)0819449598

In this paper we propose a new approach for distributed multiclass classification using a hierarchical fusion architecture. Binary decisions from local sensors, possibly in the presence of faults, axe fused locally. Locally fused results are forwarded to the global fusion center that determines the final classification result. Classification fusion in our approach is implemented via error correcting codes to incorporate fault-tolerance capability. This new approach not only provides an improved fault-tolerance capability but also reduces bandwidth requirements as well as computation time and memory requirements at the fusion center. Numerical examples axe provided to illustrate the performance of this new approach.

关键词： distributed classification decision fusion multisensor fusion error correcting codes fault-tolerance

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GStreamer as a framework for image processing applications in image fusion

GStreamer as a framework for image processing applications i...

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

作者： Burks, Stephen D. Doe, Joshua M. USA RDECOM CERDEC Night Vision & Elect Sensors Directorate Ft Belvoir VA 22060 USA

ISBN: (纸本)9780819486387

Multiple source band image fusion can sometimes be a multi-step process that consists of several intermediate image processing steps. Typically, each of these steps is required to be in a particular arrangement in order to produce a unique output image. GStreamer is an open source, cross platform multimedia framework, and using this framework, engineers at NVESD have produced a software package that allows for real time manipulation of processing steps for rapid prototyping in image fusion.

关键词： Image fusion Image processing Video MATLAB Video processing Sensors Frame grabbers Cameras Rapid manufacturing Superposition

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