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检索条件"任意字段=18th Conference on Signal and Data Processing of Small Targets"

共 390 条记录，以下是311-320 订阅

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Analysis of event-related fMRI data using best clustering bases

引用

18th International conference on Information processing in Medical Imaging, IPMI 2003

作者： Meyer, Francois G. Chinrungrueng, Jatuporn Department of Electrical Engineering University of Colorado at Boulder BoulderCO80309-0425 United States

ISBN: (纸本)3540405607

We explore a new paradigm for the analysis of event-related functional magnetic resonance images (fMRI) of brain activity. We regard the fMRI data as a very large set of time series xi(t), indexed by the position i of a voxel inside the brain. the decision that a voxel i0 is activated is based not solely on the value of the fMRI signal at i0, but rather on the comparison of all time series xi(t) in a small neighborhood Wi0 around i0. We construct basis functions on which the projection of the fMRI data reveals the organization of the time-series xi(t) into "activated", and "non-activated" clusters. these "clustering basis functions" are selected from large libraries of wavelet packets according to their ability to separate the fMRI time-series into the activated cluster and a non activated cluster. this principle exploits the intrinsic spatial correlation that is present in the data. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Magnetic resonance

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Chirp pulse microwave computed tomography(CP-MCT) equipped with a fan beam scanner for high-speed imaging of a biological target

Chirp pulse microwave computed tomography(CP-MCT) equipped w...

引用

25th Annual International conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2003

作者： Miyakawa, M. Harada, E. Jing, W. Center for Transdisciplinary Research Niigata University Niigata Japan Graduate School of Natural Science and Technology Niigata University Niigata Japan

ISBN: (纸本)0780377893

Recently, microwave imaging aiming at early-stage-tumor detection has become of major interest because of its relatively high contrast resolution in the image. Chirp pulse microwave computed tomography (CP-MCT) obtains the attenuation and/or phase shift images of biological targets by use of a chirp pulse signal from 1 GHz to 2 GHz and signal processing techniques. the experimental- and computational-studies show that the estimated spatial resolution becomes 10 to 12 mm and very small temperature variation such as 0.3 degree to 0.5 degree is detectable. Usefulness of this imaging modality increases by developing a fan beam scanner that enables fast data acquisition. In fact, it takes only a few minutes for imaging, while the prototype system takes about 90 minutes. © 2003 IEEE.

关键词： data acquisition

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Chirp pulse microwave computed tomography(CP-MCT) equipped with a fan beam scanner for high-speed imaging of a biological target

Chirp pulse microwave computed tomography(CP-MCT) equipped w...

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Annual International conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： M. Miyakawa E. Harada W. Jing Center for Transdisciplinary Research Niigata University Niigata Japan Graduate School ofNatural Science and Technology NiiRata University Niigata Japan

关键词： Chirp Biology computing Microwave imaging High-resolution imaging Spatial resolution Image resolution signal resolution Microwave theory and techniques Computed tomography Attenuation

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Detection of small IR objects using wavelets, matched subspace detectors, and registration

Detection of small IR objects using wavelets, matched subspa...

引用

14th conference on signal and data processing of small targets

作者： Hewer, G Kuo, W Kenney, C Hanson, G Bobinchak, J USN Air Warfare Ctr China Lake CA 93555 USA

ISBN: (纸本)0819444782

Infrared sensors and advanced signal processing are used to detect small (or "point") targets in highly cluttered and noisy environments. In this paper, a wavelet detection algorithm and tracking of small targets in clutter will be discussed. A new registration algorithm based on optical flow estimates with matched subspace detectors against small maneuverable targets is also discussed. Both detectors incorporate adaptive constant false alarm rate (CFAR) detection statistics. Simulation of the detection and tracking algorithms using an unclassified database with a helicopter target and platform for the video cameras is summarized.

关键词： wavelets matched subspace detector registration

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Radar detection of multiple moving targets in clutter using time-frequency-radon transform

Radar detection of multiple moving targets in clutter using ...

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14th conference on signal and data processing of small targets

作者： Chen, VC USN Res Lab Div Radar Washington DC 20375 USA

ISBN: (纸本)0819444782

In this paper, we analyze features of radar returns from moving targets, introduce the basic concept of time-frequency-Radon transforms, describe the Radon transform for line feature detection, discuss their applications to detection of multiple moving targets in clutter, and demonstrate two examples of moving target detection using simulated radar data.

关键词： time-frequency transform Radon transform moving targets multiple targets

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Target classification with data from multiple sensors

Target classification with data from multiple sensors

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14th conference on signal and data processing of small targets

作者： Drummond, OE CyberRnD Inc Culver City CA 90230 USA

ISBN: (纸本)0819444782

the methods used in the classification of multiple small targets can be very different from the methods commonly used in traditional pattern recognition. First, there may be characteristics of the features for. each target class that can permit simpler computations than other features. In addition, in classifying targets, the target tracks are updated as new data becomes available and hence there can be a sequence of feature measurements that are available for the target classification process. In addition, with multiple targets, the a priori information may be in a form that make the classification processing for one target dependent on the classification processing of other targets. these aspects of target classification that make that processing different from traditional pattern recognition are the concern of this paper. To limit the length of the paper, the scope is restricted to classification tasks that allow the linear-Gaussian assumption to be used. Also, the data used in the classification process is restricted to features, i.e., no attributes, and the assumption is the tracker does not employ feature-aided tracking. While these assumptions simplify the discussion, the methods used could be modified to permit classification of a broad scope of classification tasks.

关键词： multiple target tracking features target typing detection classification recognition identification and discrimination automatic target recognition (ATR) multiple models Bayesian methods and Kalman filter

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Bayesian approach to avoiding track seduction

Bayesian approach to avoiding track seduction

引用

14th conference on signal and data processing of small targets

作者： Salmond, DJ Everett, NO QinetiQ Farnborough GU14 0LX Hants England

ISBN: (纸本)0819444782

the problem of maintaining track on a primary target in the presence spurious objects is addressed. Recursive and batch filtering approaches are developed. For the recursive approach, a Bayesian track splitting filter is derived which spawns candidate tracks if there is a possibility of measurement misassociation. the filter evaluates the probability of each candidate track being associated with the primary target. the batch filter is a Markov-chain Monte Carlo (MCMC) algorithm which fits the observed data sequence to models of target dynamics and measurement-track association. Simulation results are presented.

关键词： Bayesian methods target tracking multiple targets JPDAF MCMC

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Alternative architectures for IMM tracking of maneuvering aircraft

Alternative architectures for IMM tracking of maneuvering ai...

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14th conference on signal and data processing of small targets

作者： Hutchins, RG Wilson, D Allred, LK Duren, R USN Postgrad Sch Monterey CA USA

ISBN: (纸本)0819444782

this paper presents the results of a study of tracking algorithms for maneuvering targets. the design focuses on alternative algorithms to track two-dimensional targets during maneuvers. the algorithms explored include a standard Kalman algorithm, an extended Kalman algorithm in which the target turn rate is an additional state variable, an interactive multiple model (IMM) algorithm consisting of two models with varying plant noise, a three-model IMM specifying three distinct target turn rates, and a constant gain alpha-beta filter. the IMM trackers tended to work the best in this study, with the three-model IMM performing the best overall.

关键词： target tracking maneuvering targets interactive multiple models

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Real-world tracking system performance evaluation

Real-world tracking system performance evaluation

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14th conference on signal and data processing of small targets

作者： Blackman, SS Dempster, RJ Raytheon Elect Syst El Segundo CA 90245 USA

ISBN: (纸本)0819444782

Preliminary tracking system design and analysis is typically done using simulated data in which the target truth is known and many techniques have been developed for evaluating performance under these conditions. However, there is a notable lack of any consistent approach for evaluating tracker performance for "real" data in which there may be an unknown number of "targets of opportunity" whose trajectories are not known. In addition, the background clutter/false alarm environment may be unknown so that an important analysis task is to determine the most accurate background models. this paper proposes a set of criteria for evaluating the tracks that are formed using "real" data collected in the field in the presence of an unknown number of "targets of opportunity". these criteria include duration, update history, and measures of kinematic and data association consistency. A scoring method is developed and the use of these criteria for system design is discussed.

关键词： multiple target tracking performance evaluation real data

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Target selection using neural networks

Target selection using neural networks

引用

14th conference on signal and data processing of small targets

作者： Özener, MS Yardimci, Y Univ Enformat Enstitusu Orta Dogu Tekn TR-06351 Ankara Turkey

ISBN: (纸本)0819444782

Target selection is the task of assigning a value or priority to various targets in a scenario. this priority is usually determined by the threat the target poses on the defender in addition to its vulnerability to possible measures to be taken by the defender. In this study, we describe a target selection technique based on neural networks. the utility or value of each target is assumed to be an unknown function acting on certain features of the target such as size, intensity, speed and direction of movement. Neural networks used in the context of function estimation is a viable candidate for determining this unknown function for generating target priorities. Various. neural network configurations are examined and simulation results are presented.

关键词： Neural networks Target detection Neurons Ranging signal processing Image processing Infrared imaging Infrared radiation Sensors databases

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