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

共 306 条记录，以下是71-80 订阅

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Decision fusion strategies for target detection with a three-sensor suite

Decision fusion strategies for target detection with a three...

引用

conference on sensor fusion - architectures, algorithms, and applications

作者： Dasarathy, BV Dynetics Inc. (United States)

ISBN: (纸本)081942482X

Boolean logic based decision fusion strategies for target detection with two sensors have been studied in detail in the literature over the years. Increasing the number of sensors to three, offers an aided dimension of flexibility in the design of fusion strategies. One could visualize a single stage fusion wherein the decision outputs of all the three sensor subsystems are fused simultaneously under a variety of strategies such as AND logic, or majority (simple or firm decisions only) logic, or a no-firm contradiction logic. Alternatively, one could explore a two-stage fusion strategy, wherein either an AND or an OR logic is used at the first stage combining the decisions of two of the sensor subsystems, followed by a similar logic choice combining the fused decision from the first level with the decision from the third sensor subsystem. Of these strategies, while some may turn out to be equivalent in a mathematical sense, others remain clearly unique. The study analyzes these strategies to assess their relative benefits. The papers concludes with a brief discussion on possible extensions in terms of temporal fusion strategies that exploit information derived from multiple looks and the potential for application to real-world problems such as mine detection.

关键词： sensor fusion decision fusion fusion strategies three-sensors suite mine detection

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Generation and fusion of multiple image representations in automatic corrosion detection algorithms used with shipboard tank video inspection systems

Generation and fusion of multiple image representations in a...

引用

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

作者： Nelson, BN Slebodnick, P Lemieux, EJ Krupa, M Preisser, R Lucas, K GEO CTRS INc Newton Ctr MA 02459 USA

ISBN: (纸本)0819444812

Coatings damage in shipboard tanks is presently assessed using "Certified Coatings Inspectors". Prior to a coatings inspector entering a tank, the tank must be emptied and certified "gas free". These requirements combined with the limited number of certified coatings inspectors available at shipyards and Naval Bases significantly increases the cost and the logistical requirements associated with performing shipboard tank inspections. There is additionally significant variation in damage assessments made by different inspectors. To overcome these difficulties, the Naval Research Laboratory has developed two video inspection systems that obviate requirements for both certifying tanks gas free and for emptying the tank prior to performing an inspection. These systems also obviate requirements for inspector presence during tank inspections. The Naval Research Laboratory has also developed an automatic corrosion detection algorithm. The corrosion detection algorithm currently employs two independent algorithms that individually assess the tank coatings damage. The independent damage assessments are than fused to attain a single coatings damage value. In testing performed to date, it has been shown that the corrosion detection algorithm significantly reduces the effect of inspector-to-inspector variability and provides an accurate assessment of tank coatings damage. This in turn makes it significantly easier to prioritize ship maintenance.

关键词： information fusion image processing automatic corrosion detection

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Data fusion multi-agent framework

Data fusion multi-agent framework

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

作者： Gatepaille, S Brunessaux, S Abdulrab, H Matra Syst & Informat F-27106 Val De Reuil France

ISBN: (纸本)0819436771

This paper describes a work currently in progress whose aim is to design, develop and evaluate a Multi-Agent Framework for Data fusion (DFMAF). This is being done with the support of a battlefield surveillance demonstrator application, named TA-10 [3,6]. Through the following chapters, we will describe the benefits of using such a Framework for data fusion problems. Firstly, we will briefly present the multi-agent research domain. Then, we will go into further details to describe DFMAF, the multi-agent framework designed to help solving data fusion problems. The appropriateness of DFMAF to data fusion problems will also be pointed out. Next, the implementation and use of DFMAF in the support application will be detailed as well as the assessment procedure followed. Finally, we will conclude and expose the future work which will be done.

关键词： data fusion battlefield surveillance multi-sensor multiple target tracking multi-agent systems distributed systems

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Intelligent fusion processing in BMD applications

Intelligent fusion processing in BMD applications

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conference on sensor fusion - architectures, algorithms, and applications

作者： McCullough, C Byrd, K Bjork, C Grider, G Smith, B Morris, N Dasarathy, B U.S. Army Space and Strategic Defense Command (United States) Nichols Research Corp. (United States) Dynetics Inc. (United States)

ISBN: (纸本)081942482X

Intelligent processing techniques are applied to a Ballistic Missile Defense (BMD) application, focused on classifying the objects in a typical threat complex, using fused IR and Ladar sensors. These techniques indicate the potential to improve designation robustness against ''off-normal''/unexpected conditions, or when sensor data or classifier performance degrades. A Fused sensor Discrimination (FuSeD) simulation testbed was assembled for designation experiments, to evaluate test and simulation data, assess intelligent processor and classification algorithms, and evaluate sensor performance. Results were produced for a variety of neural net and other nonlinear classifiers, yielding high designation performance and low false alarm rates. Most classifiers yield a few percent in false alarm rate: rates are further improved when multiple techniques are applied via a Majority Based fusion technique. Example signatures, features, classifier descriptions, intelligent controller design, and architecture ate included. Work was performed for the Discriminating Interceptor Technology Program (DITP).

关键词： sensors LIDAR Intelligent sensors Neural networks Data fusion Doppler effect Computer simulations Detection and tracking algorithms Infrared sensors Infrared signatures

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fusion under the closed-world assumption

Fusion under the closed-world assumption

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

作者： Grégoire, E Univ Sci & Tech Lille Flandres Artois CRIL F-62307 Lens France

ISBN: (纸本)0819440809

In this paper, new operators for fusing logical knowledge-bases (KBs) are proposed. They are defined in such a way that they can handle KBs that must be interpreted under forms of the closed-world assumption. Such assumptions implicitly augment the KBs with some additional information that could not be deduced using the standard logical deductive apparatus. More precisely, we extend previous recent works about the logical fusion of knowledge to handle such KBs. We focus on the model-theoretic definition of fusion operators to show their limits. In particular, the basic logical concept of model appears too coarse-grained. We solve this problem and propose new operators that cover a whole family of fusion approaches in the presence of variants of the closed-world assumption.

关键词： data fusion knowledge base fusion CWA nonmonotonic logics

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A linearly constrained least squares approach for multisensor data fusion

A linearly constrained least squares approach for multisenso...

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conference on sensor fusion - architectures, algorithms, and applications

作者： Zhou, YF Leung, H Telexis Corporation Canada Ottawa ON K1V 7P2 2427 Holly Lane Canada Surface Radar Section Defence Research Establishment Ottawa Ottawa ON K1A OK2 Canada

ISBN: (纸本)081942482X

In this paper, we present a linearly constrained least squares (LCLS) algorithm for multisensor data fusion. While fusion is considered in the scope of linear combination, the objective of the LCLS algorithm is to minimize the energy of the linearly fused information based on empirical sensory information. Statistical performance analysis of the LCLS algorithm will be carried out including the consistency and asymptotic covariance of the estimates. Effectiveness of the proposed fusion algorithm will be evaluated numerically based on fusion of signals and images.

关键词： data fusion least squares minimum variance information uncertainty multisensor tracking consistency analysis

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Performance evaluation on contour extraction using Hough transform and RANSAC for multi-sensor data fusion applications in industrial food inspection

Performance evaluation on contour extraction using Hough tra...

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20th IEEE conference on Signal Processing - algorithms, architectures, Arrangements, and applications (SPA)

作者： Kroeger, M. Sauer-Greff, W. Urbansky, R. Lorang, M. Siegrist, M. Univ Kaiserslautern Chair Commun Engeneering Kaiserslautern Germany WIPOTEC GmbH Kaiserslautern Germany

ISBN: (纸本)9788362065271

For multi-sensor data fusion applications the accurate alignment of different sensor data is essential for the proper combination of matching features. In food inspection system the boxing often is in a rectangular shape. This knowledge can be used to rectify the image data, an important step in the alignment stage. In case of low contrast between boxing and background, the detected contour may differ significantly from the actual values. In this paper the performance of the Hough transform and the RANdom SAmple Consensus (RANSAC)-algorithm are evaluated relating to the correct extraction of the boxing contour out of contour data distorted by position errors of the outer shape. The evaluation results indicate the superiority of the RANSAC algorithm with respect to scalability, robustness and execution time.

关键词： Hough transforms

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MathWeb™:: A concurrent image analysis tool suite for multi-spectral data fusion

MathWeb™:: A concurrent image analysis tool suite for multi...

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

作者： Achalakul, T Haaland, PD Taylor, S Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

ISBN: (纸本)0819431931

This paper describes a preliminary approach to the fusion of multi-spectral image data for the analysis of cervical cancer. The long-term goal of this research is to define spectral signatures and automatically detect cancer cell structures. The approach combines a multi-spectral microscope with an image analysis tool suite, MathWeb. The tool suite incorporates a concurrent Principal Component Transform (PCT) that is used to fuse the multi-spectral data. This paper describes the general approach and the concurrent PCT algorithm. The algorithm is evaluated from both the perspective of image quality and performance scalability.

关键词： concurrent computing image fusion principal component transform spectral signature

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Feature level sensor fusion

Feature level sensor fusion

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

作者： Peli, T Young, M Knox, R Ellis, K Bennett, F Atlantic Aerosp Elect Corp Waltham MA 02154 USA

ISBN: (纸本)0819431931

This paper describes two practical fusion techniques (hybrid fusion and cued fusion) for automatic target cueing that combine features derived from each sensor data at the object-level. In the hybrid fusion method each of the input sensor data is prescreened (i.e. Automatic Target Cueing (ATC) is performed) before the fusion stage. The cued fusion method assumes that one of the sensors is designated as a primary sensor, and thus ATC is only applied to its input data. If one of the sensors exhibits a higher Pd and/or a lower false alarm rate, it can be selected as the primary sensor, However, if the ground coverage can be segmented to regions in which one of the sensors is known to exhibit better performance, then the cued fusion can be applied locally/adaptively by switching the choice of a primary sensor. Otherwise, the cued fusion is applied both ways (each sensor as primary) and the outputs of each cued mode are combined. Both fusion approaches use a back-end discrimination stage that is applied to a combined feature vector to reduce false alarms. The two fusion processes were applied to spectral and radar sensor data and were shown to provide substantial False alarm reduction. The approaches are easily extendable to more than two sensors.

关键词： sensors Image fusion Data fusion Synthetic aperture radar Target detection Feature extraction sensor fusion Image processing Infrared sensors Target recognition

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A Metamaterial-Inspired Combined Inductive-Capacitive sensor

A Metamaterial-Inspired Combined Inductive-Capacitive Sensor

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conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Long, Jiang Wang, Bingnan Mitsubishi Elect Res Labs Cambridge MA 02139 USA

ISBN: (纸本)9781628410587

This paper reports a metamaterial inspired combined inductive-capacitive sensing method for detecting and distinguishing metallic and non-metallic objects. Metallic and non-metallic objects can be distinguished by measuring both of their inductive and capacitive responses based on the fact that they respond differently to inductive and capacitive sensing. The proposed method is inspired by metamaterial structures. Both inductive and capacitive sensing are simultaneously realized when the sensor is operating at off-resonant frequencies. The proposed method is demonstrated with typical printed circuit board (PCB) technology. The designed sensor can distinguish the metallic and dielectric objects with a sensing range about 10 mm, showing a competitive performance compared with commercially available proximity sensors.

关键词： proximity sensor metamaterials combined sensing

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