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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241-250 订阅

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Data level fusion using common symmetry set

Data level fusion using common symmetry set

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

作者： Tari, S Middle E Tech Univ Dept Engn Sci TR-06531 Ankara Turkey

ISBN: (纸本)0819431931

Availability of different imaging modalities requires techniques to process and combine information from different images of the same phenomena. We present a symmetry based approach for combining information from multiple images. fusion is performed at data level. Actual object boundaries and shape descriptors are recovered directly from raw sensor output(s). Method is applicable to arbitrary number of images in arbitrary dimension.

关键词： Image fusion Data fusion Image segmentation sensors Image processing Information fusion Data processing Shape analysis 3D image processing Image analysis

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Registration of scenes for the detection of concealed weapons

Registration of scenes for the detection of concealed weapon...

引用

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

作者： Slamani, MA Varshney, PK Alford, MG Ferris, D Stiefvater Consultants Inc Marcy NY 13403 USA

ISBN: (纸本)0819431931

A number of sensors are being developed for the Concealed Weapon Detection (CWD), and use of the appropriate sensor or combination of sensors will be: very important to the success of such technologies. Assuming that two identical sensors are used to collect data on a target from different angular views, this paper addresses the problem of registration associated with the collected scenes. Theory and application to real data are presented.

关键词： image registration Concealed Weapons Detection A'SCAPE enhancement fusion

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sensor fusion cognition using belief filtering for tracking and identification

Sensor fusion cognition using belief filtering for tracking ...

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

作者： Blasch, E Hong, L SNAT AFRL Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819431931

Humans exhibit remarkable abilities to estimate, filter, predict, and fuse information in target tracking tasks. To improve track quality, we extend previous tracking approaches by investigating human cognitive-level fusion for constraining the set of plausible targets where the number of targets is not known a priori. The target track algorithm predicts a belief in the position and pose for a set of targets and an automatic target recognition algorithm uses the pose estimate to calculate an accumulated target-belief classification confidence measure. The human integrates the target track information and classification confidence measures to determine the number and identification of targets. This paper implements the cognitive belief filtering approach for sensor fusion and resolves target identify through a set-theory approach by determining a plausible set of targets being tracked.

关键词： sensor fusion target recognition classification & identification tracking cognitive belief filter HRR

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Information fusion benefits delineation in off-nominal scenarios

Information fusion benefits delineation in off-nominal scena...

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

作者： Dasarathy, BV Dynet Inc Huntsville AL 35814 USA

ISBN: (纸本)0819431931

The potential problem of deterioration In recognition system performance because of imprecise, incomplete, or imperfect training is a serious challenge inherent to most real-world applications. This problem is often referred to in certain applications as degradation of performance under off-nominal conditions. This study presents the results of an investigation carried out to illustrate the scope and benefits of information fusion in such off-nominal scenarios. The research covers features in - decision out (FEI-DEO) fusion as well as decisions in - decision out (DEI-DEO) fusion. The latter spans across both information sources (sensors) and multiple processing tools (classifiers). The investigation delineates the corresponding fusion benefit domains using as an example, real-world data from an audio-visual system for the recognition of French oral vowels embedded in various levels of acoustical noise.

关键词： information fusion off-nominal scenarios audio-visual fusion vowel recognition

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Cross band pixel selection in multi-resolution image fusion

Cross band pixel selection in multi-resolution image fusion

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

作者： Petrovic, V Xydeas, C Univ Manchester Manchester Sch Engn MARC Manchester M13 9PL Lancs England

ISBN: (纸本)0819431931

The work described in this paper focuses on cross band pixel select:ion as applied to pixel level multi-resolution image fusion. In addition, multi-resolution analysis and synthesis is realised via. QMF sub-band decomposition techniques. Thus cross-band pixel selection is-considered with the aim of reducing the contrast and structural distortion image artefacts produced by existing wavelet based, pixel level, image fusion schemes. Preliminary subjective image fusion results demonstrate clearly the advantage which the proposed cross-band selection technique offers, when compared to conventional area based pixel selection.

关键词： image fusion multi-resolution image processing sensor fusion

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Fuzzy sensor fusion for gas turbine power plants

Fuzzy sensor fusion for gas turbine power plants

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

作者： Goebel, K Agogino, A GE Corp Res & Dev Niskayuna NY 12309 USA

ISBN: (纸本)0819431931

In this paper we present a methodology for fuzzy sensor fusion. We then apply this methodology to sensor data from a gas turbine power plant. The developed fusion algorithm tackles several problems: 1.) it aggregates redundant (but uncertain) sensor information;this allows making decisions which sensors land to what degree) should be considered for propagation of sensor information. 2.) It filters out noise and sensor failure from measurements;this allows a system to operate despite temporary or permanent failure of one or more sensors. For the fusion, we use a combination of direct and functional redundancy. The fusion algorithm uses confidence values obtained for each sensor reading from validation curves and performs a weighted average fusion. With increasing distance from the predicted value, readings are discounted through a non-linear validation function. They are assigned a confidence value accordingly. The predicted value in the described algorithm is obtained through application of a fuzzy exponential weighted moving average time series predictor with adaptive coefficients. Experiments on real data from a gas turbine power plant show the robustness of the fusion algorithm which leads to smooth controller input values.

关键词： fuzzy fusion fuzzy validation fuzzy monitoring diagnosis

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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...

引用

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

引用

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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ELIPS: Toward a sensor fusion processor on a chip

ELIPS: Toward a sensor fusion processor on a chip

引用

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

作者： Daud, T Stoica, A Thomas, T Li, WT Fabunmi, J CALTECH Jet Prop Lab Pasadena CA 91109 USA

ISBN: (纸本)0819431931

The paper presents the concept and initial tests from the hardware implementation of a low-power, high-speed reconfigurable sensor fusion processor. The Extended Logic Intelligent Processing System (ELIPS) processor is developed to seamlessly combine rule-based systems, fuzzy logic, and neural networks to achieve parallel fusion of sensor in compact low power VLSI. The first demonstration of the FLIPS concept targets interceptor functionality;other applications, mainly in robotics and autonomous systems are considered for the future. The main assumption behind ELIPS is that fuzzy, rule-based and neural forms of computation can serve as the main primitives of an "intelligent" processor. Thus, in the same way classic processors are designed to optimize the hardware implementation of a set of fundamental operations, ELIPS is developed as an efficient implementation of computational intelligence primitives, and relies on a set of fuzzy set, fuzzy inference and neural modules, built in programmable analog hardware. The hardware programmability allows the processor to reconfigure into different machines, taking the most efficient hardware implementation during each phase of information processing. Following software demonstrations on several interceptor data three important ELIPS building blocks (a fuzzy set preprocessor, a rule-based fuzzy system and a neural network) have been fabricated in analog VLSI hardware and demonstrated microsecond-processing times.

关键词： sensor fusion hardware sensor fusion processor fuzzy expert system neural networks reconfigurable hardware

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sensor management in an ASW data fusion system

Sensor management in an ASW data fusion system

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

作者： Penny, DE Def Evaluat & Res Agcy Malvern WR14 3PS Worcs England

ISBN: (纸本)0819431931

The Multi-sensor fusion Management (MSFM) algorithm positions multiple, detection-only, passive sensors in a two-dimensional plane to optimise the fused probability of detection using a simple decision fusion method, previously the MSFM algorithm was evaluated on two synthetic problem domains comprising of both static and moving targets(1). In the original formulation the probability distribution of the target location was modelled using a non-parametric approach. The logarithm of the fused detection probability was used as a criterion function for the optimisation of the sensor positions. This optimisation used a straightforward gradient ascent approach, which occasionally found local optima. Following the placement optimisation the sensors were deployed and the individual sensor detections combined using a logical OR fusion rule. The target location distribution could then be updated using the method of sampling, importance re-sampling (SIR). In the current work the algorithm is extended to admit a richer variety of behaviour. More realistic sensor characteristic models are used which include detection-plus-bearing sensors and false alarm probabilities commensurate with actual sonar sensor systems. In this paper the performance of the updated MSFM algorithm is illustrated on a realistic anti-submarine warfare (ASW) application(2) in which the placement of the sensors is carried out incrementally, allowing for the optimisation of both the location and the number of sensors to be deployed.

关键词： sensor fusion resource allocation anti-submarine warfare (ASW)

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