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检索条件"任意字段=Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2009"

共 283 条记录，以下是71-80 订阅

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Technical Overview of the Sarnoff Acadia II Vision Processor

Technical Overview of the Sarnoff Acadia II Vision Processor

引用

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

作者： van der Wal, Gooitzen S. Sarnoff Corp Princeton NJ 08540 USA

ISBN: (纸本)9780819481740

The Sarnoff Acadia (R) II is a powerful vision processing SoC (System-on-a-Chip) that was specifically developed to support advanced vision applications where system size, weight and/or power are severely constrained. This paper, targeted at vision system developers, presents a detailed technical overview of the Acadia (R) II, highlighting its architecture, processing capabilities, memory and peripheral interfaces. All major subsystems will be covered, including: video preprocessing, specialized vision processing cores for multi-spectral image fusion, multi-resolution contrast normalization, noise coring, image warping, and motion estimation. Application processing via the MPCore (R), an integrated set of four ARM (R) 11 floating point processors with associated peripheral interfaces is presented in detail. The paper will emphasize the programmability of the Acadia (R) II, while describing its ability to provide state-of-the-art real-time image processing in a small, power optimized package.*

关键词： Real-time Multiresolution Vision processing Image fusion Stabilization Embedded Processing Multicore multi-spectral

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Sensor management and Bayesian networks

Sensor management and Bayesian networks

引用

Conference on multisensor, multisource information fusion

作者： Yilmazer, N Osadciw, LA Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

ISBN: (纸本)0819453579

This paper introduces the sensor management problem and uses Bayesian networks as a scalable approach to handling the operational decisions concerning the sensor network. In general, single sensor systems only provide partial information on the state of the event or environment while multisensor systems provide a synergistic effect, which improves the quality and availability of information. Data fusion techniques can effectively combine this environmental information from similar and/or dissimilar sensors. Until recently, the operator could manage the systems easily, but current systems are more complex and produce data more quickly than earlier versions. A sensor manager becomes necessary when this occurs to assist the operators. Researchers have developed many single point sensor management solutions. General sensor management algorithms that can handle a variety of sensor network applications have yet to emerge.

关键词： sensor management Bayesian networks fusion

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Multi-brain fusion and applications to intelligence analysis

Multi-brain fusion and applications to intelligence analysis

引用

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

作者： Stoica, A. Matran-Fernandez, A. Andreou, D. Poli, R. Cinel, C. Iwashita, Y. Padgett, C. NASA Jet Prop Lab Pasadena CA USA

ISBN: (纸本)9780819495471

In a rapid serial visual presentation (RSVP) images are shown at an extremely rapid pace. Yet, the images can still be parsed by the visual system to some extent. In fact, the detection of specific targets in a stream of pictures triggers a characteristic electroencephalography (EEG) response that can be recognized by a brain-computer interface (BCI) and exploited for automatic target detection. Research funded by DARPA's Neurotechnology for Intelligence Analysts program has achieved speed-ups in sifting through satellite images when adopting this approach. This paper extends the use of BCI technology from individual analysts to collaborative BCIs. We show that the integration of information in EEGs collected from multiple operators results in performance improvements compared to the single-operator case.

关键词： Bain-Computer Interfaces collaborative BCI Rapid Serial Visual Presentation visual search

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Multi-Layered Context Impact Modulation for Enhanced Focus of Attention of Situational Awareness in Persistent Surveillance Systems

Multi-Layered Context Impact Modulation for Enhanced Focus o...

引用

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

作者： Shirkhodaie, Amir Rababaah, Haroun Tennessee State Univ Dept Mech & Mfg Engn Ctr Excellence Battlefield Sensor Fus Nashville TN 37209 USA

ISBN: (纸本)9780819481740

This paper presents a Multi-Layered Context Impact Modulation (MCIM) technique for persistent surveillance systems (PSS) and discusses its layered architecture for different context modulations including: spatial, temporal, sensor reliability, human presence, and environmental modulations. This paper also presents a fusion model for enhancement of focus of attention at the common operation picture (COP). The fusion model combines all the impacts from the different MCIM layers onto one unified modulated map. To test and evaluate the performance of MCIM, several experiments were conducted to modulate interaction of humans and vehicles which exhibit various normal and suspicious behaviors. The experimental results show strength of this approach in correctly modulating different suspicious situations with higher degree of certainty.

关键词： Persistent Surveillance Systems Situation Assessment Context Impact Layered Modulation Energy Logic fusion Engine Large-scale Sensor Networks Soft fusion

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Sensitivity of fusion performance to classifier model variations

Sensitivity of fusion performance to classifier model variat...

引用

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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Product-based multiresolution image fusion

Product-based multiresolution image fusion

引用

Conference on multisensor, multisource information fusion

作者： Ostrem, T Kozaitis, SP Florida Inst Technol Dept Elect & Comp Engn Melbourne FL 32901 USA

ISBN: (纸本)0819457981

We combined images from different sensors that were enhanced by multiscale products of the wavelet coefficients. Using the wavelet transform, we used a multiresolution analysis to form products of coefficients across scales. Then, a fusion rule was applied to the product images to determine how the original images could be combined. Using this approach, we were able to decrease the sensitivity of the fusion process to noise.

关键词： multiresolution image processing sensor fusion wavelet transform

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Novel classification fusion techniques for military target classification

Novel classification fusion techniques for military target c...

引用

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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INFORM Lab: a testbed for high-level information fusion and resource management

INFORM Lab: a testbed for high-level information fusion and ...

引用

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

作者： Valin, Pierre Guitouni, Adel Bosse, Eloi Wehn, Hans Happe, Jens Def R&D Canada Valcartier Decis Support Syst Sect C2 2459 Blvd Pie 11 Nord Quebec City PQ G3J 1X5 Canada MacDonald Dettwiler & Associates Ltd Richmond BC V6V 2J3 Canada

ISBN: (纸本)9780819486387

DRDC Valcartier and MDA have created an advanced simulation testbed for the purpose of evaluating the effectiveness of Network Enabled Operations in a Coastal Wide Area Surveillance situation, with algorithms provided by several universities. This INFORM Lab testbed allows experimenting with high-level distributed information fusion, dynamic resource management and configuration management, given multiple constraints on the resources and their communications networks. This paper describes the architecture of INFORM Lab, the essential concepts of goals and situation evidence, a selected set of algorithms for distributed information fusion and dynamic resource management, as well as auto-configurable information fusion architectures. The testbed provides general services which include a multilayer plug-and-play architecture, and a general multi-agent framework based on John Boyd's OODA loop. The testbed's performance is demonstrated on 2 types of scenarios/vignettes for 1) cooperative search-and-rescue efforts, and 2) a noncooperative smuggling scenario involving many target ships and various methods of deceit. For each mission, an appropriate subset of Canadian airborne and naval platforms are dispatched to collect situation evidence, which is fused, and then used to modify the platform trajectories for the most efficient collection of further situation evidence. These platforms are fusion nodes which obey a Command and Control node hierarchy.

关键词： surveillance information fusion distributed fusion software agents simulation testbed

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Adaptive multimodal biometric fusion algorithm using particle swarm

Adaptive multimodal biometric fusion algorithm using particl...

引用

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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Spatial Voting For Automatic Feature Selection, fusion, and Visualization

Spatial Voting For Automatic Feature Selection, Fusion, and ...

引用

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

作者： Jaenisch, Holger Handley, James Licht Strahl Engineering Inc. (United States) Johns Hopkins Univ. (United States) Alabama A&M Univ. (United States)

ISBN: (纸本)9780819495471

We present a novel feature selection, fusion, and visualization utility using Spatial Voting (SV). This SV feature optimization utility is designed to be an off-line stand-alone utility to help an investigator find useful feature pairs for cluster analysis and lineage identification. The analysis can be used to enable the analyst to vary parameters manually and explore the best combination that yields visually appealing or significant groups or spreading of data points depending on the planned use of the analysis downstream. Several different criteria are available to the user in order to determine the best SV grid size and feature pair including minimizing zeros, minimizing covariance, balanced minimum covariance, or the maximization of one of eight different scoring metrics: Containment, Rand Index, Purity, Precision, Recall, F-Score, Normalized Mutual information (NMI), and Adjusted Rand Index (ARI). The tool that is described in this work facilitates this analysis and makes it simple, efficient, and interactive if the analyst so desires.

关键词： Spatial Voting Automatic Feature Selection fusion Visualization NMI Rand Index ARI

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