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检索条件"任意字段=Multisensor. Multisource Information Fusion: Architectures, Algorithms, and Applications 2003"

共 284 条记录，以下是51-60 订阅

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Cognitive engineering in algorithm development for multisensor.data fusion in military applications

Cognitive engineering in algorithm development for multisens...

引用

Conference on multisensor. multisource information fusion

作者： Kight, AC Narayanan, S Wright State Univ Dept Biomed Ind & Human Factors Engn Dayton OH 45435 USA

ISBN: (纸本)0819453579

In battlefield situations, human operators are bombarded with substantial amounts of information and expected to make near-instantaneous decisions. The large amounts of information, coupled with short decision times and the need to reduce the potential of making incorrect decisions, create the possibility for information overload. This problem is especially prominent in military applications involving imagery from multiple sensors. Computer-based algorithms for fusing pertinent sets of imagery have proven somewhat useful for alleviating this problem. However, little research has been done on designing multisensor.data fusion systems using principles of cognitive engineering, which involves the consideration of human cognition during the design process. The design of a sensor fusion system using principles from cognitive engineering would create a more natural relationship between human and machine, and would thus be extremely effective in reducing operator error in military situations. This paper explores the need for integrating human reasoning and cognition in algorithm development for multisensor.fusion applications.

关键词： Algorithm development Data fusion Defense technologies Cognition Image fusion Error analysis Image sensors Sensor fusion Sensors

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Optimal interval estimation fusion based on sensor interval estimates and confidence degrees

Optimal interval estimation fusion based on sensor interval ...

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Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2003

作者： Zhu, YM Li, BH Sichuan Univ Dept Math Chengdu 610064 Peoples R China

ISBN: (纸本)0819449598

The interval estimation fusion method based on sensor interval estimates and their confidence degrees is developed. When sensor estimates are independent of each other, a combination rule to merge sensor estimates and their confidence degrees is proposed. Moreover, two popular optimization-criteria: minimizing interval length with an allowable minimum confidence degree, or maximizing confidence degree with an allowable maximum interval length are suggested. In terms of the two criteria, an optimal interval estimation fusion can be obtained based on the combined intervals and their confidence degrees. Then we can extend the results on the combined interval outputs and. their confidence degrees to obtain a conditional combination rule and the corresponding optimal fault-tolerant interval estimation fusion in terms of the-two criteria. It is easy to see that Marzullo's fault-tolerant interval estimation fusion(11) is a special case of our method. We also point out that in some sense, our combination rule is similar to the combination rule in Dempster-Shafer evidence theory. However, the confidence degrees given in this paper is summable, but they (called mass function in Dempster-Shafer evidence theory) are not there;therefore, Dempster-Shafer's combination rule is not applicable to the interval estimation fusion.

关键词： interval estimation confidence degree combination ride optimal interval estimation fusion

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Data fusion in road traffic engineering: An overview

Data fusion in road traffic engineering: An overview

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Conference on multisensor. multisource information fusion

作者： El Faouzi, NE ENTPE INRETS Transport & Traff Engn Lab F-69675 Bron France

ISBN: (纸本)0819453579

The objective of this paper is to present an analysis of recent applications of data fusion (DF) in road traffic engineering. First, we report the most significant applications of data fusion techniques in road traffic engineering area: traffic monitoring, signal control, Automatic Incident Detection, traffic forecasting, Intelligent Transportation Systems..., as well as the extent and direction of DF interest it the field. Second, a classification including applications, fusion goals and mathematical tools is proposed.

关键词： traffic engineering data fusion ITS theory of evidence Lalman filtering estimation fusion

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Current research on wavelet-based image fusion algorithms

Current research on wavelet-based image fusion algorithms

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Conference on multisensor. multisource information fusion

作者： Li, HH Guo, L Liu, H Northwestern Polytech Univ Coll Automat Xian 710072 Peoples R China

ISBN: (纸本)0819457981

Wavelet transform is efficiently applied to the area of image fusion because it's properties such as multiresolution analysis, accurate reconstruction and similarity to people's vision understanding. On the basis of reviewing the former research, the fusion results may be better than those with previous common fusion algorithms in many applications. This paper describes the principle and method of wavelet-based image fusion and analyzes it's current research and future trend from the two respects: the modality of wavelet transform and fusion rules.

关键词： wavelet transform image fusion multi-band wavelet wavelet package

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STAC: A Comprehensive Sensor fusion Model for Scene Characterization

STAC: A Comprehensive Sensor Fusion Model for Scene Characte...

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

作者： Kira, Zsolt Wagner, Alan R. Kennedy, Chris Zutty, Jason Tuell, Grady Georgia Tech Res Inst Atlanta GA 30332 USA

ISBN: (纸本)9781628416145

We are interested in data fusion strategies for Intelligence, Surveillance, and Reconnaissance (ISR) missions. Advances in theory, algorithms, and computational power have made it possible to extract rich semantic information from a wide variety of sensors, but these advances have raised new challenges in fusing the data. For example, in developing fusion algorithms for moving target identification (MTI) applications, what is the best way to combine image data having different temporal frequencies, and how should we introduce contextual information acquired from monitoring cell phones or from human intelligence? In addressing these questions we have found that existing data fusion models do not readily facilitate comparison of fusion algorithms performing such complex information extraction, so we developed a new model that does. Here, we present the Spatial, Temporal, Algorithm, and Cognition (STAC) model. STAC allows for describing the progression of multi-sensor raw data through increasing levels of abstraction, and provides a way to easily compare fusion strategies. It provides for unambiguous description of how multi-sensor data are combined, the computational algorithms being used, and how scene understanding is ultimately achieved. In this paper, we describe and illustrate the STAC model, and compare it to other existing models.

关键词： multisensor.fusion data fusion scene characterization scene understanding

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Classification of terrain using multi-resolution satellite/aerial imagery and LiDAR data

Classification of terrain using multi-resolution satellite/a...

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

作者： Kocher, Brian R. Thomas, Alan M. Georgia Inst Technol Georgia Tech Res Inst Atlanta GA 30332 USA

ISBN: (纸本)9780819481740

High resolution LiDAR data is used to augment spectral data to improve resolution/accuracy. Digital elevation information, texture information, and spectral data are all combined into a single dataset and different clustering algorithms are used on the raster information and compared with clusters of spectral data alone. Long term goals of the work are to find efficient and effective methods of combining different data sets of varying resolution from different sources into a single dataset for analysis to improve data and classification resolution and accuracy.

关键词： image fusion image processing texture multispectral imagery lidar data material classification

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Learned fusion Operators Based on Matrix Completion

Learned Fusion Operators Based on Matrix Completion

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

作者： Risko, Kelly K. D. Hester, Charles F. US Army Res Dev & Engn Command Weap Dev & Integrat Directorate Aviat & Missile Res Dev & Engn Ctr Redstone Arsenal AL 35898 USA

ISBN: (纸本)9780819486387

The efficient and timely management of imagery captured in the battlefield requires methods capable of searching the voluminous databases and extracting highly symbolic concepts. When processing images, a semantic and definition gap exists between machine representations and the user's language. Based on matrix completion techniques, we present a fusion operator that fuses imagery and expert knowledge provided by user inputs during post analysis. Specifically, an information matrix is formed from imagery and a class map as labeled by an expert. From this matrix an image operator is derived for the extraction/prediction of information from future imagery. We will present results using this technique on single mode data.

关键词： fusion matrix completion class map

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Image fusion for remote sensing using fast, large-scale neuroscience models

Image fusion for remote sensing using fast, large-scale neur...

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

作者： Brumby, Steven P. Los Alamos Natl Lab Los Alamos NM 87545 USA

ISBN: (纸本)9780819486387

We present results with large-scale neuroscience-inspired models for feature detection using multi-spectral visible/infrared satellite imagery. We describe a model using an artificial neural network architecture and learning rules to build sparse scene representations over an adaptive dictionary, fusing spectral and spatial textural characteristics of the objects of interest. Our results with fast codes implemented on clusters of graphical processor units (GPUs) suggest that visual cortex models are a promising approach to practical pattern recognition problems in remote sensing, even for datasets using spectral bands not found in natural visual systems.

关键词： Visual cortex sparse coding artificial neural network

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Integration of language and sensor information

Integration of language and sensor information

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Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2003

作者： Perlovsky, LI Weijers, B Air Force Res Lab Bedford MA 01731 USA

ISBN: (纸本)0819449598

The talk describes the development of basic technologies of intelligent systems fusing data from multiple domains and leading to automated computational techniques for understanding data contents. Understanding involves inferring appropriate decisions and recommending proper actions, which in turn requires fusion of data and knowledge about objects, situations, and actions. Data might include sensory data, verbal reports, intelligence intercepts, or public records, whereas knowledge ought to encompass the whole range of objects, situations, people and their behavior, and knowledge of languages. In the past, a fundamental difficulty in combining knowledge with data was the combinatorial complexity of computations, too many combinations of data and knowledge pieces had to be evaluated. Recent progress in understanding of natural intelligent systems, including the human mind, leads to the development of neurophysiologically motivated architectures for solving these challenging problems, in particular the role of emotional neural signals in overcoming combinatorial complexity of old logic-based approaches. Whereas past approaches based on logic tended to identify logic with language and thinking, recent studies in cognitive linguistics have led to appreciation of more complicated nature of linguistic models. Little is known about the details of the brain mechanisms integrating language and thinking. Understanding and fusion of linguistic information with sensory data represent a novel challenging aspect of the development of integrated fusion systems. The presentation will describe a non-combinatorial approach to this problem and outline techniques that can be used for fusing diverse and uncertain knowledge with sensory and linguistic data.

关键词： information fusion language sensors intelligent systems understanding linguistic models knowledge non-combinatorial cognitive neural

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Multi-channel nonlinear phase analysis for time frequency data fusion

Multi-channel nonlinear phase analysis for time frequency da...

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Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2003

作者： Mavandadi, S Aarabi, P Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada

ISBN: (纸本)0819449598

A general method for time delay of arrival (TDOA) estimation for time-frequency information fusion is analyzed. This technique, for which the generalized cross correlation method and histogram methods are special cases, results in a low TDOA estimation error And high efficiency in computation. The proposed method relies on a non-linear phase-error selector function, which acts as a reward and punish method for the phase error at each frequency. Three different selector function candidates, consisting of cosine, rectangular, and triangular functions are analyzed using simulations. In the presence of Gaussian noise, the rectangular selector function performs better than the cosine at signal-to-noise ratios (SNRs) higher than 10dB while for lower SNRs the cosine function performs better. With speech noise, the cosine function, which corresponds to the generalized cross correlation technique, has higher anomaly percentages and higher root-mean-square errors than the rectangular function. This suggests, that in general, the rectangular selector function, which can be computed more easily than the cosine selector function, is superior technique to the generalized cross correlation method for. real-time applications.

关键词： delay-of-arrival estimation time-frequency data fusion microphone arrays speech processing

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