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检索条件"任意字段=Multisensor, Multisource Information Fusion: Architecture, Algorithms, and Applications 2005"

共 73 条记录，以下是31-40 订阅

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Dynamic resource management for adaptive distributed information fusion in large volume surveillance

Dynamic resource management for adaptive distributed informa...

引用

Conference on multisensor, multisource information fusion

作者： Farahbod, Roozbeh Glasser, Uwe Welm, Hans Simon Fraser Univ Software Technol Lab Burnaby BC V5A 1S6 Canada MDA Corp Res & Dev Richmond BC Canada

ISBN: (纸本)9780819471659

We propose a highly adaptive and auto-configurable, multi-layer network architecture for distributed information fusion to address large volume surveillance challenges, assuming a multitude of different sensor types on multiple mobile platforms for intelligence, surveillance and reconnaissance. Our focus is on network enabled operations to efficiently manage and improve employment of a set of mobile resources, their information fusion engines and networking capabilities under dynamically changing and essentially unpredictable conditions. A high-level model of the proposed architecture is formally described in abstract functional and operational terms based on the Abstract State Machine formalism. This description of the underlying design concepts provides a concise and precise blueprint for reasoning about key system attributes at an intuitive level of understanding.

关键词： distributed systems sensor networks dynamically configurable systems resource management network architecture abstract state machines formal specification high level design

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Advanced algorithms for distributed fusion

Advanced algorithms for distributed fusion

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Conference on multisensor, multisource information fusion

作者： Gelfand, A. Smith, C. Colony, M. Bowman, C. Pei, R. Huynh, T. Brown, C. Decis Analyt Corp 1235 S Clark StSuite 400 Arlington VA 22202 USA Data Fus Neural Networks Broomfield CO 80020 USA US Army CERDEC Intelligence & Informat Warfare Directorat Ft Monmouth NJ USA

ISBN: (纸本)9780819471659

The US Military has been undergoing a radical transition from a traditional "platform-centric" force to one capable of performing in a "Network-Centric" environment. This transformation will place all of the data needed to efficiently meet tactical and strategic goals at the warfighter's fingertips. With access to this information, the challenge of fusing data from across the batttlespace into an operational picture for real-time Situational Awareness emerges. In such an environment, centralized fusion approaches will have limited application due to the constraints of real-time communications networks and computational resources. To overcome these limitations, we are developing a formalized architecture for fusion and track adjudication that allows the distribution of fusion processes over a dynamically created and managed information network. This network will support the incorporation and utilization of low level tracking information within the Army Distributed Common Ground System (DCGS-A) or Future Combat System (FCS). The framework is based on Bowman's Dual Node Network (DNN) architecture that utilizes a distributed network of interlaced fusion and track adjudication nodes to build and maintain a globally consistent picture across all assets.

关键词： distributed data fusion decentralized data fusion consistency assessment performance evaluation resource management Dual Node Network (DNN)

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A field demonstration of multi-INT surveillance and data fusion

A field demonstration of multi-INT surveillance and data fus...

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Conference on multisensor, multisource information fusion

作者： Na, Arthur Havens, Steve Argon ST (United States)

ISBN: (纸本)9780819471659

Collecting data in any domain is often only the first step in creating intelligence. This is the beginning of a process which includes fusing that data with other data sources to create something more than the individual data elements. This has been historically difficult because collection sensors are optimized for their respective conventional domains. We have developed a multi-sensor system combining an electro-optical camera and infi-ared camera, using a revolutionary data handling and manipulating process to fuse multiple types of data to create inteffigence. To address the data fusion needs of such a system, we have developed an internationally recognized, open data fusion language called Transducer Markup Language (TML). TML was used in conjunction with the multi-sensor system to describe data from the EO and IR cameras and support sensors all within a self-contained mobile delivery system during mifitary exercises in July 2007. The TML data was collected and disseminated to multiple users within a Service Oriented architecture (SOA), after which it was Ruther distributed using Cursor-On-Target (COT) messages over a second network. This demonstrated both data fusion of multiple sensor data sources and integration into existing data distribution infrastructures. Key innovations of this demonstration included the use of multiple sensors including EO & IR cameras and a single sensor data exchange language to capture and describe sensor output.

关键词： sensor fusion Transducer Markup Language sensor network SOA sensor actuator data exchange standard common data model common sensor model sensor ontology

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Proceedings of SPIE - multisensor, multisource information fusion: architectures, algorithms, and applications 2007

Proceedings of SPIE - Multisensor, Multisource Information F...

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multisensor, multisource information fusion: architectures, algorithms, and applications 2007

ISBN: (纸本)081946693X

The proceedings contain 27 papers. The topics discussed include: a novel method to evaluate the performance of pan-sharpening algorithms;signal-to-noise ratio for cross-sensor fusion approach;fusion and kernel type selection in adaptive image retrieval;merging infrared and color visible images with a contrast enhanced fusion method;multi-sensor detection and fusion technique;novel classification fusion techniques for military target classification;a full-scale prototype multisensor system for fire detection and situational awareness;fusion of disparate information sources in a hybrid decision-support architecture;selection of fusion operations using rank-score diversity for robot mapping and localization;maximum likelihood ensemble filter applied to multisensory systems;assessing the value of information in a fuzzy cognitive map;and multisensor fusion of images for target identification.

关键词： information fusion

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fusion of disparate information sources in a hybrid decision-support architecture

Fusion of disparate information sources in a hybrid decision...

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Conference on multisensor, multisource information fusion

作者： Braun, Jerome J. Glina, Yan Brattain, Laura MIT Lincoln Lab 244 Wood St Lexington MA 02420 USA

ISBN: (纸本)9780819466938

Disparity and uncertainty of information sources are both significant problems in information fusion. This paper investigates the problem of disparity in general, and in conjunction with FLASH - a hybrid information-fusion cognitive-processing approach we developed. Different forms of disparity are identified and their categorization is presented, and their implications on the information fission process are discussed. The issue of feature-level vs. decision-level fusion is investigated, and the methods of coping with disparity within FLASH are presented. Source uncertainty estimation techniques are discussed as well. Disparity studies and the results of computational experiments related to them are presented. These studies are suggestive of the potential of the FLASH hybrid approach for fusion of disparate information sources.

关键词： information fusion machine intelligence disparity uncertainty. biodefense

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Collective agents interpolative integral (CAII) for asymmetric threat detection

Collective agents interpolative integral (CAII) for asymmetr...

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Conference on multisensor, multisource information fusion

作者： Zhu, Qiuming O'Hara, Stephen Simon, Michael Lindahl, Eric Petrov, Plamen Univ Nebraska Dept Comp Sci Omaha NE 68182 USA 21st Century Syst Inc Omaha NE 68106 USA

ISBN: (纸本)9780819466938

This paper presents a reasoning system that pools the judgments from a set of inference agents with information from heterogeneous sources to generate a consensus opinion that reduces uncertainty and improves knowledge quality. The system, called Collective Agents Interpolation Integral (CAII), addresses a high level data fusion problem by combining, in a mathematically sound manner, multi-models of inference in knowledge intensive multi agent architecture. Two major issues are addressed in CAII. One is the ability of the inference mechanisms to deal with hybrid data inputs from multiple information sources and map the diverse data sets to a uniform representation in an objective space of reasoning and integration. The other is the ability of the system architecture to allow the continuous and discrete outputs of a diverse set of inference agents to interact, cooperate, and integrate.

关键词： intelligent agents information fusion multi-model inference uncertainty reduction asymmetric threat detection

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A full-scale prototype multisensor system for fire detection and situational awareness

A full-scale prototype multisensor system for fire detection...

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Conference on multisensor, multisource information fusion

作者： Minor, Christian P. Johnson, Kevin J. Rose-Pehrsson, Susan L. Owrutsky, Jeffrey C. Wales, Stephen C. Steinhurst, Daniel A. Gottuk, Daniel T. Novo Res Inc 1900 Eikin StSuite 230 Alexandria VA 22308 USA US Naval Res Lab Washington DC 20375 USA Hughes Associates Inc Baltimore MD 21227 USA

ISBN: (纸本)9780819466938

A data fusion-based, multisensory detection system, called "Volume Sensor", was developed under the Advanced Damage Countermeasures (ADC) portion of the US Navy's Future Naval Capabilities program (FNC) to meet reduced manning goals. A diverse group of sensing modalities was chosen to provide an automated damage control monitoring capability that could be constructed at a relatively low cost and also easily integrated into existing ship infrastructure. Volume Sensor employs an efficient, scalable, and adaptable design framework that can serve as a template for heterogeneous sensor network integration for situational awareness. In the development of Volume Sensor, a number of challenges were addressed and met with solutions that are applicable to heterogeneous sensor networks of any type. These solutions include: 1) a uniform, but general format for encapsulating sensor data, 2) a communications protocol for the transfer of sensor data and command and control of networked sensor systems, 3) the development of event specific data fusion algorithms, and 4) the design and implementation of modular and scalable system architecture. In full-scale testing on a shipboard environment, two prototype Volume Sensor systems demonstrated the capability to provide highly accurate and timely situational awareness regarding damage control events while simultaneously imparting a negligible footprint on the ship's 100 Mbps Ethernet network and maintaining smooth and reliable operation in a real-time fashion.

关键词： fire detection flood detection multisensor multicriteria data fusion multivariate analysis video sensor audio sensor spectral sensor sensor network

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Proceedings of SPIE: multisensor, multisource information fusion: architectures, algorithms, and applications 2005

Proceedings of SPIE: Multisensor, Multisource Information Fu...

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multisensor, multisource information fusion: architecture, algorithms, and applications 2005

The proceedings contain 35 papers from the conference on multisensor, multisource information fusion: architectures, algorithms, and applications 2005. Topics discussed include: reduced data projection slice image fusion using principal component analysis;real-time implementation of image alignment and fusion;image fusion with the hybrid evolutionary algorithm and response analysis;a perceptual quality metric for image fusion based on regional information;multispectral sensor fusion using the projection-slice theorem;a situation awareness model applied to multiple domains;hybrid framework for fusion 2+ in multi-multi air engagement;and product-based multiresolution image fusion.

关键词： Sensor data fusion

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Hybrid methods for multisource information fusion and decision support

Hybrid methods for multisource information fusion and decisi...

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Conference on multisensor, multisource information fusion

作者： Braun, Jerome J. Glina, Yan MIT Lincoln Lab 244 Wood St Lexington MA 02173 USA

ISBN: (纸本)0819462985

This paper presents the progress of an ongoing research effort in multisource information fusion for biodefense decision support. The effort concentrates on a novel machine-intelligence hybrid-of-hybrids decision support architecture termed FLASH (fusion, Learning, Adaptive Super-Hybrid) we proposed. The highlights of FLASH discussed in the paper include its cognitive-processing orientation and the hybrid nature involving heterogeneous multiclassifier machine learning and approximate reasoning paradigms. Selected specifics of the FLASH internals, such as its feature selection techniques, supervised learning, clustering, recognition and reasoning methods, and their integration, are discussed. The results to date are presented, including the background type determination and bioattack detection computational experiments using data obtained with a multisensor fusion testbed we have also developed. The processing of imprecise information originating from sources other than sensors is considered. Finally, the paper discusses applicability of FLASH and its methods to complex battlespace management problems such as course-of-action decision support.

关键词： multisource information fusion machine intelligence cognitive processing decision support biodefense

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Fuselets - An agent based architecture for fusion of heterogeneous information and data

Fuselets - An agent based architecture for fusion of heterog...

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Conference on multisensor, multisource information fusion

作者： Beyerer, Juergen Heizmann, Michael Sander, Jennifer Fraunhofer IITB Inst Informat & Datenverarbeitung Fraunhoferstr 1 D-76131 Karlsruhe Germany

ISBN: (纸本)0819462985

A new architecture for fusing information and data from heterogeneous sources is proposed. The approach takes criminalistics as a model. In analogy to the work of detectives, who investigate crimes, software agents are instantiated that pursue clues and try to consolidate or to dismiss hypotheses. Like their human pendants, they can, if questions beyond their competencies arise, consult expert agents. Within the context of a certain task, region, and time interval, specialized operations are applied to each relevant information source, e. g. IMINT, SIGINT, ACINT,..., HUMINT*, databases etc. in order to establish hit lists of first clues. Each clue is described by its pertinent facts, uncertainties, and dependencies in form of a local degree-of-belief (DoB) distribution dagger in a Bayesian sense. For each clue, an agent is instantiated which cooperates with other agents and experts. Expert agents support the use of different information sources. Consultation of experts capable of accessing certain information sources results in changes of the DoB of the pertinent clue. According to the significance of concentration of their DoB distribution, clues are abandoned or pursued further to formulate task specific hypotheses. Communication between the agents serves to find out whether different clues belong to the same cause and thus can be combined. At the end of the investigation process, the different hypotheses are evaluated by a jury and a final report is created that constitutes the fusion result. The approach proposed avoids calculating global DoB distributions by adopting a local Bayesian approximation and thus reduces the complexity of the problem essentially. Different information sources are transformed into DoB distributions using the maximum entropy paradigm and considering known facts as constraints. Nominal, ordinal, and cardinal quantities can be treated within this framework equally. The architecture is scalable by tailoring the number of agents according t

关键词： heterogeneous information sources Bayesian fusion agent technology criminalistics local Bayesian approach artificial intelligence man machine interaction representation of uncertainty

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