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

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sensor data fusion with support vector machine techniques

Sensor data fusion with support vector machine techniques

引用

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

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

ISBN: (纸本)0819444812

This paper presents an approach to multisensor data fusion based on the use of Support Vector Machines (SVM). The approach is investigated using simulated generic sensor data, representative of data imperfections that may be encountered in multisensor fusion applications. In particular the issue of data incompleteness is addressed and a method exploiting vicinity of training points is proposed for incompleteness correction. The paper also investigates applicability of vicinal kernels in SVM-based sensor data fusion.

关键词： multisensor data fusion Support Vector Machines data incompleteness machine learning recognition

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Decision fusion using fuzzy integral method

Decision fusion using fuzzy integral method

引用

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

作者： Liang, JM Yang, WH Cai, XY Xidian Univ Sch Elect Engn Xian 710071 Shaanxi Peoples R China

ISBN: (纸本)0819436771

It is an intuitionistic demand for multisensor decision fusion processes that the degree of importance of each sensor's local decision towards the final decision should reflect adequately its detection, identification or classification ability, especially in time variant environments. This can be seen clearly in distributed detection systems, where the optimal final decision is the weighed sum of the local decisions, and the weights are functions of the local sensor's detection and false alarm probabilities. When voting fusion strategy is used, it supposes in nature that all the sensors are working at the same performance level. When dealing with soft decision fusion problems, the local sensor's reports represent its uncertainty about the observed phenomena. The most commonly used approaches for soft decision fusion are Bayesian probability theory and Dempster-Shafer evidence theory. Both of them update the evidence using the sensors' reports only, the reliability differences between the decision-making sensors are not considered. In this paper, the decision fusion ability of fuzzy integral is investigated from the viewpoints of both hard decisions and soft decisions. When fuzzy integral is used to fuse multisensor decisions, the fuzzy density can be interpreted as the importance of each sensor's local decision rewards the final decision. Fuzzy densities can be subjectively assigned by experts, or be induced form data set. We present a learning algorithm to distinguish the degree of importance of each sensor's local decision. A genetic algorithm-based hybrid learning method is used to determine the fuzzy densities from the training data set. A multi-pattern classification experiment is simulated to validate our proposed method.

关键词： multisensor decision fusion hard decision soft decision fuzzy measure fuzzy integral fuzzy density genetic algorithms

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Information fusion concepts. From information elements definition to the application of fusion approaches

Information fusion concepts. From information elements defin...

引用

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

作者： Solaiman, B Ecole Natl Super Telecommun Bretagne Dept ITI F-29285 Brest France

ISBN: (纸本)0819440809

The aim of this gaper is to give a homogeneous and a simple framework in order to present information fusion concepts. The main concept presented here concerns the definition of the information element concept This concept is then illustrated through the general scheme of pattern recognition systems. Different types of information imperfection are then illustrated. Finally, information fusion concepts and fusion architectures are illustrated

关键词： information element data fusion decision fusion model fusion

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Process performance monitoring by using information fusion in a high volume consumer electronics manufacturing process.

Process performance monitoring by using information fusion i...

引用

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

作者： Asp, S Wide, P Univ Orebro AASS Res Grp Dept Technol & Sci Orebro Sweden

ISBN: (纸本)0819436771

As production volumes continue to increase and the global market for consumer electronics is getting fiercer, the need for a reliable and essentially fault-free production process is becoming a necessity to survive. The manufacturing processes of today are highly complex and the increasing amount of process data is making it hard to unravel the useful information extracted from a huge data set. In general, high volume manufacturing processes often increase the need for more sensor data which require new approaches of measuring technologies in order to increase the overall process knowledge. However, the analysis of huge data sets of process information has become more important, e.g. how do we extract the information features and fuse different information in order to optimize a process and reduce the overall data amount. A process performance monitoring application for a high volume consumer electronics manufacturing process, by using multivariate information fusion techniques, has been developed. The purpose of the monitoring system is to identify test stations deviating in measurement values from other test stations and to provide early warning and identification of important process related disturbances, malfunctions or faults by extracting information by sensor measurements and by using knowledge about the process.

关键词： process performance monitoring high volume manufacturing information fusion multivariable analysis SPC MSPC

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SCENE CLASSIFICATION AND SEGMENTATION USING MULTISPECTRAL sensor fusion IMPLEMENTED WITH NEURAL NETWORKS 4

SCENE CLASSIFICATION AND SEGMENTATION USING MULTISPECTRAL SE...

引用

4th International conference on applications of Artificial Neural Networks

作者： LAZOFSON, LE KUZMA, TJ BATTELLE MEM INST COLUMBUSOH 43201

ISBN: (纸本)0819412015

Near-simultaneous, multispectral, coregistered imagery of ground target and background signatures were collected over a full diurnal cycle in the MWIR, LWIR, near-infrared, blue, green, and red wavebands using Battelle's portable sensor suite. The imagery data were processed with classical statistical algorithms and artificial neural networks to discriminate target signatures from background clutter and investigate automatic target detection and recognition schemes.

关键词： Neural networks Image processing Image segmentation Artificial neural networks Data processing Image fusion Detection and tracking algorithms Network architectures sensor fusion sensors

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Edge detection through information fusion using fuzzy and evidential reasoning concepts

Edge detection through information fusion using fuzzy and ev...

引用

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

作者： Solaiman, B Lecornu, L Roux, C ENST Bretagne Dpt ITI F-29285 Brest France

ISBN: (纸本)0819436771

The main topic of this study concerns edge detection using information fusion approaches. Edge detection methods are based on first and second order local operations followed by a thresholding and edge tracking techniques. In this study, an intermediate fuzzy-evidential conceptual level is introduced between the gray level and edge detection symbolic information level. From the image, evidences concerning edges and regions are extracted using fuzzy membership functions as well as contextual information. The proposed approach can be decomposed into two steps: 1) application of evidential reasoning approach in order to compute a basic masse function, 2) edge detection process based on the use of an iterative algorithm, exploiting the contextual information and a belief masse function. Masse function computation is based of the use of edge and region fuzzy membership functions of each pixel in the analyzed scene. The main interest of this step is to consider membership functions as being observed evidences instead of image gray level values. The key idea of the second step is to use all the information about regions, edges and contextual data in the edge extraction process. Obtained results are encouraging and the proposed methodology is shown to be robust to different noisy environments.

关键词： evidential reasoning fuzzy edge detection evidential fusion information fusion

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Multi-level enhanced target identification fusion method

Multi-level enhanced target identification fusion method

引用

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

作者： Ku, JK Ock, SY LG Innotek Co. Ltd. (South Korea)

ISBN: (纸本)0819444812

Data fusion architecture can be categorized into data-level fusion, feature-level fusion and decision-level fusion by its characteristics. In this paper, we provide a new target identification fusion technology in which we adopt not only feature-level fusion approach but also decision-level fusion approach in order to consider even sensors' uncertain reports and improve fusion performance. In feature-level fusion stage, we applied fuzzy set theory and Bayesian theory based on the sensor data, such as sensor parameter and detected target information. In decision-level fusion stage, we applied advanced Bayesian theory to decide final target identification. Experimental results with various kinds of sensor data have verified the robustness of our algorithms comparing with conventional feature-level, decision-level fusion algorithms.

关键词： multi-level data fusion fuzzy set theory Bayesian method target identification

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Impact of expanding the multiplicity of information sources on fusion system architecture and fusion logic options

Impact of expanding the multiplicity of information sources ...

引用

conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Dasarathy, BV

ISBN: (纸本)0819449598

Various fusion system architectures postulated and studied previously for environments with two and three data sources are further explored in this study to bring out the expanding scope for delineating the architecture options for multiple data source environments. A spectrum of single and multi-stage fusion architecture options are defined. The potential for such expansion of choices is illustrated using the scenario with four data sources as an example. Potential problem environments corresponding to this range of two to four data sources are identified. Various fusion logic strategies that can be brought to bear for the analysis of these fusion architecture options, when these fusion architectures are employed for Decisions In - Decision Out (DEI-DEO) fusion, are also discussed.

关键词： sensor fusion decision fusion fusion strategies multi-sensor suites

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Multifeature fusion using Pulse Coupled Neural Networks

Multifeature fusion using Pulse Coupled Neural Networks

引用

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

作者： Inguva, R Johnson, JL Schamschula, MP East West Enterprises Huntsville AL 35805 USA

We propose an unbiased multifeature fusion Pulse Coupled Neural Network (PCNN) algorithm. The method shares linking between several PCNNs running in parallel. We illustrate the PCNN fusion technique with a clean and n... 详细信息

ISBN: (纸本)0819431931

关键词： Image fusion Neural networks Image processing Modulators Convolution Evolutionary algorithms Feature extraction Modulation Pulse generators Transform theory

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Multiple sensor fusion for long range surveillance: Design and performance issues

Multiple sensor fusion for long range surveillance: Design a...

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conference on sensor fusion - architectures, algorithms, and applications

作者： Jones, G Raytheon Canada Ltd. (Canada)

ISBN: (纸本)081942482X

This paper provides a description and detailed review of a multiple hypothesis tracking system, which handles data from two radars, and a number of other sources. An efficient method for processing detections from two (time-offset) radars, and integrating them in the multiple hypothesis framework will be described. The implications of such a methodology on the tracking filter will also be discussed. The paper then explains the algorithm employed for fusion of Automatic Dependent Surveillance reports into the system, and concludes with a demonstration of some sample results.

关键词： multiple-hypothesis tracking sensor fusion

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