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检索条件"主题词=Algorithm Development"

共 1737 条记录，以下是1491-1500 订阅

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EXTRACTION OF TEXT BOXES FROM ENGINEERING DRAWINGS

EXTRACTION OF TEXT BOXES FROM ENGINEERING DRAWINGS

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CONF ON MACHINE VISION APPLICATIONS IN CHARACTER RECOGNITION AND INDUSTRIAL INSPECTION

作者： CHAI, I DORI, D Univ. of Kansas (United States) Technion/Israel Institute of Technology (Israel)

ISBN: (纸本)0819408158

Textboxes are minimum size rectangles enclosing blocks of text in engineering drawings. Their separation from the graphics surrounding them is a first step in character recognition, and is a part of the Machine Drawing Understanding System, currently under development. Textbox extraction is preceded by orthogonal zig-zag vectorization, arc segmentation, and arrowhead recognition. It is done by clustering the remaining short bars that are located close to each other through a region growing process. Further refinements follow which improve the ability of the process to outline the real textboxes.

关键词： Visualization Standards development Tolerancing Optical character recognition Raster graphics algorithm development Computer aided design Hough transforms Image segmentation Information visualization

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A 1.32 MICRON, LONG-RANGE, SOLID-STATE, IMAGING LADAR 2

A 1.32 MICRON, LONG-RANGE, SOLID-STATE, IMAGING LADAR

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CONF ON SENSORS AND SENSOR SYSTEMS FOR GUIDANCE AND NAVIGATION 2

作者： ANDRESSEN, CC Hercules Defense Electronics Systems Inc. (United States)

ISBN: (纸本)081940859X

The design of a newly designed ladar system (called LADAR) using a diode-pumped Q-switched Nd:YLF laser operating at 1.32 micron is described, and images obtained with the LADAR are presented together with the performance results of signal processing algorithms. It is shown that the system is able to obtain a range image of a target at 2 km, obtain intensity image information, and implement target detection and identification algorithms.

关键词： LIDAR Sensors Semiconductor lasers Electronics algorithm development Receivers Imaging systems Detection and tracking algorithms Eye Target detection

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IMAGING IN DIFFUSING MEDIA WITH A NEURAL NET FORMULATION - A PROBLEM IN LARGE-SCALE COMPUTATION

IMAGING IN DIFFUSING MEDIA WITH A NEURAL NET FORMULATION - A...

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CONF ON PHYSIOLOGICAL MONITORING AND EARLY DETECTION DIAGNOSTIC METHODS

作者： SCHLERETH, FH FOSSACECA, JM KECKLER, AD BARBOUR, RL Syracuse Univ. (United States) SUNY/Brooklyn Health Science Ctr. (United States)

ISBN: (纸本)0819407879

Attempts to recover images from objects which diffuse radiation pose an especially challenging problem in terms of defining a suitable reconstruction algorithm and with regard to identifying an appropriate computing environment for efficient processing. In this paper we consider both issues and, in particular, describe results of an algebraic technique for imaging the interior of objects which diffuse penetrating radiation using a new multicomputer environment. Two important issues which arise when considering the numerical solution of ultra large problems are the numerical precision achieved and the overall computing efficiency. Our interest in this problem concerns the possibility of obtaining 3-D optical images of tissue which could identify the availability of oxygen by evaluating oxygen- dependent changes in the near infrared spectrum of hemoglobin. These studies were motivated by recent reports from our group and others, which showed promising results for imaging in dense scattering media given only diffusely scattered signals. In our model we assume the use of an NIR laser to provide the input radiation and suitable detectors to measure both transmission and backscatter. In our present work we assume a simple Markov process model for the way in which the energy travels in the medium, but it should be noted that the reconstruction technique we propose can use any model, including nonlinear as well as linear effects, and higher order processes. Current simulations are in 2-D but the methods are easily extended to 3-D. The algorithms we propose are more closely related to algebraic reconstruction algorithms such as ART, SIRT, and SART than to algorithms based on the Born and Rytov approximations such as used for tomographic imaging with diffracting sources. Our algorithms are a significant departure from those based on these standard algebraic methods. We assume only a probabilistic knowledge of the path of the radiation, and minimal knowledge of the absorption

关键词： Neural networks Absorption Reconstruction algorithms Computing systems Backscatter Scattering Telecommunications algorithm development Image analysis Tomography

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DATA FUSION OF OUTPUTS PROVIDED BY A DISTRIBUTED FIELD OF PASSIVE SENSORS

DATA FUSION OF OUTPUTS PROVIDED BY A DISTRIBUTED FIELD OF PA...

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4TH CONF ON THE SIGNAL AND DATA PROCESSING OF SMALL TARGETS 1992

作者： JEWITT, TW General Atronics Corp. (United States)

ISBN: (纸本)0819408638

As a result of an on-going IR&D effort, General Atronics Corporation (GAC) has developed effective algorithms for automatic acquisition, tracking, and recognition of multiple targets - broadly referred to as Automatic Target Recognition (ATR) - using passive sensors on board multiple distributed platforms. The goal of AIR is to either provide timely and accurate assistance to a human operator, who is the ultimate decision maker, or he totally autonomous in extracting the necessary information, its processing, and final decision making. Applications of this technology include Electro-Optical Fire Control Systems (EOFCS), Infrared Search and Track (IRST), Infrared Counter Measures (IRCM), Covert Aircraft Recovery and Tracking Systems (CARTS), Strategic Defense Initiative (SDI), Anti-Submarine Warfare (ASW), Battlefield Intelligence, and Security.

关键词： Sensors Detection and tracking algorithms Target detection Data processing Target recognition Passive sensors Signal processing algorithm development Automatic target recognition Data fusion

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ANOMALY DETECTION IN DATA USING NEURAL NETWORKS WITH NATURAL-SELECTION

ANOMALY DETECTION IN DATA USING NEURAL NETWORKS WITH NATURAL...

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1ST CONF ON SCIENCE OF ARTIFICIAL NEURAL NETWORKS

作者： DESSERT, PE Carnegie Group Inc. (United States)

ISBN: (纸本)0819408751

Frequently, time series data taken off machines contains erroneous data points due to errors in the measurement of the data. One such instance of measuring devices recording anomalies occurs in the `crash testing' of vehicles. In this task, senors are placed on the vehicle and the `crash dummy' and the vehicle is then crashed into a barrier. Force and acceleration data is collected which an engineer inspects for anomalies, correcting those that are found. Artificial neural network (ANN) technology was successfully applied to this problem to eliminate the cost and delay of this manual process. To apply ANN technology in this domain, two technical problems needed to be resolved; the appropriate network architecture and the size of the input set. These two issues are quite common and must be addressed in the development of any neural network application. To resolve both issues, I employed a machine learning algorithm that simulates the Darwinian concept of `survival of the fittest' known as the genetic learning algorithm (GLA). By combining the strength of the GLA and ANNs, a network architecture was created that `optimized' the size, speed, and accuracy of the ANN. This `hybridized' system also used the GLA to determine the `smallest' number of inputs into the ANN that were necessary to detect anomalies in data. This algorithm is known as GENENET, and is described in this paper.

关键词： Neural networks Genetics Neurons Artificial neural networks Network architectures Genetic algorithms Evolutionary algorithms algorithm development Sensors Measurement devices

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AIRBORNE MINEFIELD DETECTION SYSTEM USING IR SENSING 2

AIRBORNE MINEFIELD DETECTION SYSTEM USING IR SENSING

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CONF ON SURVEILLANCE TECHNOLOGIES 2

作者： CLOUD, E DUVOISIN, H MAKSYMONKO, G Martin Marietta Corp. (United States) U.S. Army Belvoir Research Development and Engineering Ctr. (United States)

ISBN: (纸本)0819408581

This paper describes the work completed by Martin Marietta in support of the U.S. Army's standoff minefield detection system, advanced technology transition demonstration. This paper discusses the high priority and urgent need for the standoff mine detection system within the Army Combat Engineers, it presents the results of the successful application of non developmental technology/hardware in an airborne mine/minefield detection system, and it discusses the significant payoff of applying advanced ATR and high speed parallel processing. The technologies discussed include the IR imager as the source of mine imagery, advanced image processing algorithms including neural nets, and a high speed parallel processor unique to Martin Marietta called GAPP (geometric arithmetic parallel processor).

关键词： Land mines Image processing Standoff detection Sensors Unmanned aerial vehicles Neural networks Computing systems Parallel computing Video algorithm development

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PRACTICAL PHASE UNWRAPPING OF HOLOGRAPHIC INTERFEROGRAMS 4

PRACTICAL PHASE UNWRAPPING OF HOLOGRAPHIC INTERFEROGRAMS

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CONF ON LASER INTEROMETRY 4 : COMPUTER-AIDED INTERFEROMETRY

作者： BROWN, GM Ford Motor Co. (United States)

ISBN: (纸本)0819406813

Although fully automated phase unwrapping of stepped phase interferograms is a worthy goal and is receiving considerable attention, this Utopian circumstance has not yet been uniquely achieved in a reasonable time on complex real life structures such as an automotive powertrain. The method presented here uses a binary bad spot mask and a seed point mask to phase unwrap the underlying modulo 2(pi) phase map of very complicated structures. Fringe amplitude, modulation, and triangular unit cell path dependence are used to automatically create a portion of the mask. Partition lines are added manually to the mask to separate sheared fringe systems, structural boundaries, and regions of sampling theorem violation.

关键词： Phase shift keying Binary data Image processing Holography Modulation algorithm development Laser interferometry Computing systems Data conversion Holograms

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LUCI, A PORTABLE SOFTWARE PACKAGE FOR DIFFERENT FIELDS OF IMAGE-PROCESSING RESEARCH

LUCI, A PORTABLE SOFTWARE PACKAGE FOR DIFFERENT FIELDS OF IM...

引用

CONF ON IMAGE PROCESSING AND INTERCHANGE : IMPLEMENTATION AND SYSTEMS

作者： BELLON, E WAMBACQ, P SCHOETERS, F LUCKERMANS, S MARCHAL, G SUETENS, P Katholieke Univ. Leuven (Belgium)

ISBN: (纸本)0819408131

A software package to support advanced research in the field of image processing and image analysis must have sufficiently powerful features, especially if it is to be used in a variety of application domains. In this contribution, we present the concepts of the LUCI image processing package, which has been developed in order to meet requirements that have been formulated as a result of previous experiences in our research group. These include support for multi-dimensional images and programming constructs to perform operations on those pixels that are contained in areas of arbitrary shape. In addition, we briefly present support tools for managing this software and its documentation.

关键词： Image processing 3D image processing Computer programming Software development Image compression Document management algorithm development Human-machine interfaces Image analysis Standards development

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MODIFIED BACKPROPAGATION NEURAL NETWORK WITH APPLICATIONS TO IMAGE COMPRESSION 3

MODIFIED BACKPROPAGATION NEURAL NETWORK WITH APPLICATIONS TO...

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3RD ANNUAL INTERNATIONAL CONF ON APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS

作者： KENUE, SK General Motors Research Labs. (United States)

ISBN: (纸本)0819408743

The back-propagation neural network algorithm is an iterative technique for learning the relationship between an input and output. This algorithm has been successfully used in many real-world applications; however, it suffers from slow convergence problems and can get struck in local minima of the weight-error surface. A generalization of previously proposed activation functions has been developed using a free parameter for improved convergence. A modified algorithm based on these function is suggested by bounding the input data to the derivative evaluation in the backwards pass. The modified algorithm has demonstrated superior performance on the standard parity and encoder problems. Finally, a histogram normalization technique is presented for image data compression for improved convergence.

关键词： Image compression Computer programming Evolutionary algorithms Signal to noise ratio Neural networks Artificial neural networks algorithm development Matrices Data compression Neurons

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APPLICATION OF NEURAL NETWORKS TO HYPERSPECTRAL IMAGE-ANALYSIS AND INTERPRETATION 3

APPLICATION OF NEURAL NETWORKS TO HYPERSPECTRAL IMAGE-ANALYS...

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3RD ANNUAL INTERNATIONAL CONF ON APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS

作者： SHEN, SS HORBLIT, BD Lockheed Palo Alto Research Lab. (United States)

ISBN: (纸本)0819408743

The newest airborne and spaceborne imaging sensors, unlike their predecessors, generate data at tens to hundreds of wavelengths simultaneously. The advent of these imaging spectrometers greatly increases the detail of the information available to the analyst, but the concomitant disadvantages of vastly increased data volume and complexity have stimulated the search for more efficient and accurate hyperspectral data exploitation techniques. This paper describes two neural network models used in conjunction to analyze hyper-spectral image data. The first neural network is based on an unsupervised backward error propagation model. This network generates without supervision low dimensional discriminant feature vectors from the original high dimensional signals. These features are analyzed by the second neural network, which is a layered feed-forward neural network based on statistical principles, namely Parzen window density estimation and Bayes decision rule. This network estimates class-conditional probability density functions using training samples and classifies data points so that the expected risk is minimized. Results of applying these two neural networks to 210-band AVIRIS data are presented.

关键词： Neural networks Image analysis Data modeling Statistical analysis Artificial neural networks Spectral resolution Absorption algorithm development Hyperspectral imaging Spectrometers

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