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检索条件"主题词=Algorithm development"

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NEURAL NETWORKS FOR PROCESSING DATA FROM MULTIPLE REDUNDANT SENSORS FOR MINE SYSTEMS MANAGEMENT, OPERATION, MAINTENANCE, AND CONTROL 6

NEURAL NETWORKS FOR PROCESSING DATA FROM MULTIPLE REDUNDANT ...

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CONF ON SENSOR FUSION 6

作者： GORDON, A CHANG, H KING, R Colorado School of Mines (United States)

ISBN: (纸本)0819413240

We have developed a neural-network approach to classifying signals by fusing information from multiple sensors. During the past three years, we have developed concepts and algorithms for an intelligent decision support system (IDSS) for mine managers. The goal of the IDSS is to detect the activities of machines in an underground coal mine and to produce management reports similar to traditional industrial engineering time studies. The data we operate on is power usage of the various machines taken every 50 milliseconds. Currently we are working with data from three machines which interact with each other: a continuous miner and two shuttle cars. Detection of events was first done using numerical techniques to arrive at locally best guesses and rule-based techniques to fuse the information from the different machines. Our current research involves dynamic recurrent neural networks (a variation of recurrent cascade correlation) which replace the numerical and rule-based techniques. Our current neural networks can accurately label approximately 90% of the machine events in the training set and approximately 70% in new data sets. Neural network techniques are able to adjust to the dynamic mine environment much better than the previous algorithms, consequently, the neural network approach is more acceptable in the applications environment.

关键词： Neural networks Mining Sensor fusion Sensors Land mines Signal processing algorithm development Control systems Decision support systems Intelligence systems

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IDENTIFICATION OF PASSIVE MILLIMETER-WAVE IMAGES USING NEURAL NETWORKS 4

IDENTIFICATION OF PASSIVE MILLIMETER-WAVE IMAGES USING NEURA...

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4th International Conference on Applications of Artificial Neural Networks

作者： SUNDSTROM, B MIN, K USAF WRIGHT LABEGLIN AFBFL 32542

ISBN: (纸本)0819412015

Recent developments in passive millimeter-wave imaging technology are remarkable. Images of objects obtained through clouds and fog are almost indistinguishable from similar scenes taken under clear conditions. Of particular interest is the ability to image metal targets beneath camouflage, tents, polymers, wooden shelters, and certain levels of ceramic materials. A brief description of this emerging technology will be followed by several convincing examples of images to support the claims made above. Once image formation is complete, the technique of identifying objects in the image using neural networks is similar to the schemes utilized in previous Wright Laboratory Armament directorate implementations of Automatic Target Identification work for electro-optical and infrared images.

关键词： Neural networks Extremely high frequency Passive millimeter wave imaging Sensors Artificial neural networks Infrared imaging algorithm development Staring arrays Imaging systems Visible radiation

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MAXIMIZING RUN-TIME PERFORMANCE OF DEPLOYED DATA-FLOW GRAPHS ON A MULTIPROCESSOR ARCHITECTURE

MAXIMIZING RUN-TIME PERFORMANCE OF DEPLOYED DATA-FLOW GRAPHS...

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CONF ON ARCHITECTURE, HARDWARE, AND FORWARD-LOOKING INFRARED ISSUES IN AUTOMATIC TARGET RECOGNITION

作者： TOBIAS, RJ HUNT, PD Loral/Rolm Computer Systems Inc. (United States)

ISBN: (纸本)0819411930

This paper discusses a practical solution for supporting the deployment of data flow graphs onto the Loral/Rolm Computer Systems, Inc. vector processing multi-processor architecture. It outlines the support software (both workstation hosted and target system hosted) that is required to design, debug, and maximize deployed data flow graph performance on the multiprocessor architecture. The deployment process guarantees real-time deadlines, minimizes run time scheduling overhead, and minimizes designer partitioning input. It is known that determining effective run time data flow graph node schedules for multi-processor architectures is an NP-complete class of problem not well suited to real-time systems. Loral/Rolm Computer Systems, Inc.'s vector processing toolset recognizes this problem and this paper discusses a prescheduling and pre-assignment approach for partitioning data flow graphs to available hardware resources. In particular the toolset components (which are based upon an enhanced data flow graph language) of workstation pre-assignment, prescheduling, run time gross allocation and local compute element dispatching are discussed in detail.

关键词： Cerium Computing systems Computer architecture Data modeling Switches algorithm development Databases Operating systems Data processing Signal processing

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BACKGROUND AND TARGET RANDOMIZATION AND ROOT MEAN-SQUARE (RMS) BACKGROUND MATCHING USING A NEW DELTA-T METRIC DEFINITION 3

BACKGROUND AND TARGET RANDOMIZATION AND ROOT MEAN-SQUARE (RM...

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CONF ON CHARACTERIZATION, PROPAGATION, AND SIMULATION OF SOURCES AND BACKGROUNDS 3

作者： CHOE, HC MEITZLER, T GERHART, G Battelle Memorial Institute (United States) U.S. Army Tank-Automotive Research Development and Engineering Ctr. (United States)

ISBN: (纸本)0819412031

EO/IR/Laser detection of a target amidst clutter/background is a difficult problem often treated with simplistic models. Unlike noise, clutter is more complex, neither spectrally white nor statistically Gaussian. Therefore, it is insufficient to lump clutter with noise and use standard detection curves. Battelle has produced image randomization software called BATRAN (Background and Target Randomization) which computes various types of statistical distributions to randomize background and target pixels separately. The types of statistics implemented include exponential, Gaussian, log-normal, and Rice distributions for both the background and target. In an effort to identify a more robust and accurate (Delta) T metric definition for background and target matching, Battelle also developed a new (Delta) T metric definition and its equation using RMS pixel-based higher order statistics for the background and target signature pixel data in a scene image. This new (Delta) T metric provides a better estimate of true signature difference between the background/clutter and target, enabling more accurate matching of the background/clutter and target for use in sensor detection performance assessment.

关键词： Target detection algorithm development Computer simulations Sensors Detection and tracking algorithms Silicon Electro optical modeling Electroluminescence Imaging systems Information operations

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COMPARISON OF OPTIMIZATION PROCEDURES FOR 2X2 SINCLAIR, 2X2 GRAVES, 3X3 COVARIANCE, AND 4X4 MUELLER (SYMMETRICAL) MATRICES IN COHERENT RADAR POLARIMETRY AND ITS APPLICATION TO TARGET VERSUS BACKGROUND DISCRIMINATION IN MICROWAVE REMOTE-SENSING AND IMAGING

COMPARISON OF OPTIMIZATION PROCEDURES FOR 2X2 SINCLAIR, 2X2 ...

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CONF ON RADAR POLARIMETRY

作者： LIU, CL ZHANG, X YAMAGUCHI, YS EOM, HJ BOERNER, WM Univ. of Illinois/Chicago (United States)

ISBN: (纸本)0819409219

Basic principles of radar polarimetry are introduced and various optimization procedures for the propagation (scattering) range operator equation and the received power expressions are presented and compared. Based on a complete description of isolated and distributed scatterers, target classification, target-versus-clutter discrimination, and optimal contrast enhancement algorithms are derived and shown to be of great utility in the proper interpretation of POL-RAD/SAR microwave signatures in terrestrial and planetary remote sensing.

关键词： Polarization Polarimetry Radar Scattering Matrices Optical spheres Information operations Antennas algorithm development Remote sensing

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MODELING EFFECTS OF LAND-USE ON CARBON STORAGE IN THE FORESTS OF THE PACIFIC-NORTHWEST, USA - THE CHALLENGE FOR REMOTE-SENSING

MODELING EFFECTS OF LAND-USE ON CARBON STORAGE IN THE FOREST...

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CONF ON GROUND SENSING

作者： COHEN, WB FIORELLA, M MAIERSPERGER, TK USDA Forest Service (United States)

ISBN: (纸本)0819411779

Within the context of a study to model the effects of land use on carbon storage in the Pacific Northwest region of the United States we are processing about 100 Landsat images. The image processing challenges within the study are numerous. To determine the utility of our proposed methods many of them are being tested on a 1.2 Mha area within the region. The major challenges include mapping of forest cover type and seral stage, radiometric and geometric rectification, and change detection. In this paper we present preliminary results.

关键词： Remote sensing Carbon Data modeling Earth observing sensors algorithm development Image processing Satellites Vegetation Landsat Satellite imaging

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EXPLOITING MASSIVE PARALLELISM IN algorithm UNDERSTANDING FOR AUTOMATIC TARGET RECOGNITION ON SAR IMAGERY

EXPLOITING MASSIVE PARALLELISM IN ALGORITHM UNDERSTANDING FO...

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CONF ON ARCHITECTURE, HARDWARE, AND FORWARD-LOOKING INFRARED ISSUES IN AUTOMATIC TARGET RECOGNITION

作者： DIAS, L SANTAPIETRO, JJ David Sarnoff Research Ctr. (United States)

ISBN: (纸本)0819411930

We present a novel approach for implementing and optimizing an Automatic Target Recognition (ATR) algorithm for Synthetic Aperture Radar (SAR) imagery using the Princeton Engine (PE), a general purpose massively parallel single instruction multiple data (SIMD) machine. This approach was developed in the algorithm Understanding Laboratory (AUL), a unique facility which is chartered to assist algorithm developers through high-speed implementation and near real-time visualization, and is located within the National Information Display Laboratory (NIDL). The PE architecture automatically provides a high speed-up directly proportional to the width of the image being processed, thereby reducing the train/test cycle times of ATR algorithms from days and hours down to minutes. Given this speed-up, the user can now train the system to classify a set of objects and then test it rapidly, thus tightening the train/test loop. With our approach, one can operate on the entire image, retaining useful image information until the very last stage in the algorithm.

关键词： algorithm development Detection and tracking algorithms Image processing Synthetic aperture radar Automatic target recognition Video Visualization Signal processing Distance measurement Video processing

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INSPECTION OF TIRE TREAD DEFECTS USING IMAGE-PROCESSING AND PATTERN-RECOGNITION TECHNIQUES

INSPECTION OF TIRE TREAD DEFECTS USING IMAGE-PROCESSING AND ...

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Conference on Vision, Sensors, and Control for Automated Manufacturing Systems

作者： CHEN, P SHUBINSKY, G JAN, KH CHEN, CA SIDLA, O POLZLEITNER, W NORTHWESTERN UNIV BIRLEVANSTONIL 60201

ISBN: (纸本)0819413283

An image acquisition and processing algorithm for inspection of tire treads has been developed. The tire treads are flat strips of black rubber material used as the main component in retreading automobile tires. These treads have a complex molded design on one side (DESIGN SIDE) and a flat surface on the other side. The inspection of the Design Side of the tread is one of the key operations in the tread fabrication process impacting quality and consistency of the final product. This paper will discuss development of the main optical inspection algorithms utilized in the system design. The algorithms described in this paper were tested in the laboratory prototype of the inspection system and will be implemented in the final production system.

关键词： Inspection algorithm development Detection and tracking algorithms Image processing Databases Image acquisition Defect detection Defect inspection Pattern recognition Prototyping

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DATA FUSION THROUGH SIMULATED ANNEALING OF REGISTERED RANGE AND REFLECTANCE IMAGES

DATA FUSION THROUGH SIMULATED ANNEALING OF REGISTERED RANGE ...

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CONF ON SENSOR FUSION AND AEROSPACE APPLICATIONS

作者： BECKERMAN, M SWEENEY, FJ Oak Ridge National Lab. (United States)

ISBN: (纸本)0819411922

In this paper we present results of a study of registered range and reflectance images acquired using a prototype amplitude-modulated cw laser radar. Ranging devices such as laser radars represent new technologies which are being applied in aerospace, nuclear and other hazardous environments where remote inspections, 3D identifications, and measurements are required. However, data acquired using devices of this type may contain non-stationary, signal- dependent noise, range-reflectance crosstalk, and low-reflectance range artifacts. Low level fusion algorithms play an essential role in achieving reliable performance by handling the complex noise, systematic errors, and artifacts. The objective of our study is the development of a stochastic fusion algorithm which takes as its input the registered image pair and produces as its output a reliable description of the underlying physical scene in terms of locally smooth surfaces separated by well-defined depth discontinuities. To construct the algorithm we model each image as a set of coupled Markov random fields representing pixel and several orders of line processes. Within this framework we (i) impose local smoothness constraints, introducing a simple linearity property in place of the usual sums over clique potentials; (ii) fuse the range and reflectance images through line process couplings; and (iii) use nonstationary, signal- dependent variances, adaptive thresholding, and a form of Markov natural selection. We show that the resulting algorithm yields reliable results even in worst-case scenarios.

关键词： Reflectivity Image fusion Fusion energy Image processing Sensor fusion Aerospace engineering Data fusion algorithm development LIDAR algorithms

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STAR-TRACKER BASED, ALL-SKY, AUTONOMOUS ATTITUDE DETERMINATION

STAR-TRACKER BASED, ALL-SKY, AUTONOMOUS ATTITUDE DETERMINATI...

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1ST CONF ON SPACE GUIDANCE, CONTROL, AND TRACKING

作者： DEANTONIO, L UDOMKESMALEE, S ALEXANDER, J BLUE, R DENNISON, E SEVASTON, G SCHOLL, M Jet Propulsion Lab. (United States)

ISBN: (纸本)081941185X

An automatic star identification program, which has previously been demonstrated only in computer simulation, has been integrated and tested with the tracker test lab prototype star tracker at Table Mountain Observatory. Thirteen of sixteen sky frames were matched correctly with no a priori attitude knowledge. The cause of failure in the frames that failed was determined to be algorithmic, and the flaws in the algorithm causing the failure were identified. The methodology of both Table Mountain Observatory test runs and computer simulated test runs are described, as well as results and recommendations.

关键词： Stars Detection and tracking algorithms Tolerancing Monte Carlo methods Observatories Computer simulations algorithm development Charge-coupled devices Calibration Prototyping

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