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检索条件"主题词=Detection and tracking algorithms"

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Gaussian Weighted Neighborhood Connectivity of Nonlinear Line Attractor for Learning Complex Manifolds 26

Gaussian Weighted Neighborhood Connectivity of Nonlinear Lin...

引用

Conference on Optical Pattern Recognition XXVI

作者： Aspiras, Theus H. Asari, Vijayan K. Sakla, Wesam Univ Dayton Dayton OH 45469 USA WPAFB Air Force Res Lab Fairborn OH USA

ISBN: (纸本)9781628415933

The human brain has the capability to process high quantities of data quickly for detection and recognition tasks. These tasks are made simpler by the understanding of data, which intentionally removes redundancies found in higher dimensional data and maps the data onto a lower dimensional space. The brain then encodes manifolds created in these spaces, which reveal a specific state of the system. We propose to use a recurrent neural network, the nonlinear line attractor (NLA) network, for the encoding of these manifolds as specific states, which will draw untrained data towards one of the specific states that the NLA network has encoded. We propose a Gaussian-weighted modular architecture for reducing the computational complexity of the conventional NLA network. The proposed architecture uses a neighborhood approach for establishing the interconnectivity of neurons to obtain the manifolds. The modified NLA network has been implemented and tested on the Electro-Optic Synthetic Vehicle Model Database created by the Air Force Research Laboratory (AFRL), which contains a vast array of high resolution imagery with several different lighting conditions and camera views. It is observed that the NLA network has the capability for representing high dimensional data for the recognition of the objects of interest through its new learning strategy. A nonlinear dimensionality reduction scheme based on singular value decomposition has found to be very effective in providing a low dimensional representation of the dataset. Application of the reduced dimensional space on the modified NLA algorithm would provide fast and more accurate recognition performance for real time applications.

关键词： Neurons Neural networks Databases Brain Data modeling Light sources and illumination detection and tracking algorithms Network architectures Cameras Principal component analysis

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Modeling of linewidth measurement in SEMs using advanced Monte Carlo software

Modeling of linewidth measurement in SEMs using advanced Mon...

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Conference on Metrology, Inspection, and Process Control for Microlithography XX

作者： Babin, S. Borisov, S. Ivanchikov, A. Ruzavin, I. Abeam Technol Castro Valley CA USA

ISBN: (纸本)0819461954

Accurate measurement of linewidth is a critical problem in sub-100 nm semiconductor manufacturing, where required accuracy is in the range of 1 nm and below. CD-SEMs are usually used for such measurements. A cross-correlation of CD-SEMs, while demonstrating a good relative trend, is often subject to a significant absolute linewidth error, as well as the parameters of the SEM settings being used. There is no proven algorithm for edge detection in CD-SEMs. Tool manufacturers set up the edge detection voluntarily, as a rule, which is why the absolute errors in measurement occur. In this paper, we demonstrate that edge detection depends greatly on parameters of SEM settings, like beam diameter, and pattern properties, like the wall angle of a pattern. When both the signal and pattern are known, an offset for a specific SEM algorithm can be found. An algorithm for automatic edge detection in CD-SEMs can be tuned for beam parameters and the type of pattern. A SEM signal was simulated using the advanced Monte Carlo software CHARIOT, which is commercially available. Input data for the modeling was 3D microstructures and e-beam parameters. A simulated signal was then compared to a known pattern. Such a comparison allowed us to define the edge position and calibrate a SEM so that any system- and pattern-dependent errors could be removed.

关键词： Scanning electron microscopy Monte Carlo methods Edge detection detection and tracking algorithms Silicon Calibration 3D modeling Scattering Signal detection Data modeling

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Modern Steganalysis Can Detect YASS

Modern Steganalysis Can Detect YASS

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Conference on Media Forensics and Security II

作者： Kodovsky, Jan Pevny, Tomas Fridrich, Jessica SUNY Binghamton Dept Elect & Comp Engn Binghamton NY 13902 USA Czech Tech Univ Agent Technol Ctr Dept Cybernet Prague Czech Republic

ISBN: (纸本)9780819479341

YASS is a steganographic algorithm for digital images that hides messages robustly in a key-dependent transform domain so that the stego image can be subsequently compressed and distributed as JPEG. Given the fact that state-of-the-art blind steganalysis methods of 2007, when YASS was proposed, were unable to reliably detect YASS, in this paper we steganalyze YASS using several recently proposed general-purpose steganalysis feature sets. The focus is on blind attacks that do not capitalize on any weakness of a specific implementation of the embedding algorithm. We demonstrate experimentally that twelve different settings of YASS can be reliably detected even for small embedding rates and in small images. Since none of the steganalysis feature sets is in any way targeted to the embedding of YASS, future modifications of YASS will likely be detectable by them as well.

关键词： Steganalysis Calibration detection and tracking algorithms Databases Steganography Image compression Dubnium Error analysis Quantization Feature extraction

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Strategies for cloud top phase determination - Differentiation between thin cirrus clouds and snow in manual (ground truth) analyses

Strategies for cloud top phase determination - Differentiati...

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Conference on Satellite Remote Sensing and Modeling of Clouds and the Atmosphere

作者： Hutchison, KD Etherton, BJ Topping, PC Lockheed Martin Missiles & Space Co. Inc. (United States)

ISBN: (纸本)0819423653

Quantitative assessments on the performance of automated cloud analysis algorithms require the creation of highly accurate, manual cloud,no cloud (CNC) images from multispectral meteorological satellite data. In general, the methodology to create ground truth analyses for the evaluation of cloud detection algorithms is relatively straightforward. However, when focus shifts toward quantifying the performance of automated cloud classification algorithms, the task of creating ground truth images becomes much more complicated since these CNC analyses must differentiate between water and ice cloud tops while ensuring that inaccuracies in automated cloud detection are not propagated into the results of the cloud classification algorithm, The process of creating these ground truth CNC analyses may become particularly difficult when little or no spectral signature is evident between a cloud and its background, as appears to be the case when thin cirrus is present over snow-covered surfaces. In this paper, procedures are described that enhance the researcher's ability to manually interpret and differentiate between thin cirrus clouds and snow-covered surfaces in daytime AVHRR imagery. The methodology uses data in up to six AVHRR spectral bands, including an additional band derived from the daytime 3.7 micron channel, which has proven invaluable for the manual discrimination between thin cirrus clouds and snow. It is concluded that while the 1.6 micron band is needed to distinguish between snow and water clouds in daytime data, the 3.7 micron channel remains essential to differentiate between thin ice clouds and snow. However, this capability that may be lost if the 3.7 micron data switches to a nighttime-only transmission with the launch of future NOAA satellites.

关键词： Clouds detection and tracking algorithms Solar energy Analytical research Atmospheric optics Channel projecting optics Image classification Meteorological satellites Multispectral imaging Satellites

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CONTROL OF FLEXIBLE, KINEMATICALLY REDUNDANT ROBOT MANIPULATORS

CONTROL OF FLEXIBLE, KINEMATICALLY REDUNDANT ROBOT MANIPULAT...

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CONF ON COOPERATIVE INTELLIGENT ROBOTICS IN SPACE

作者： NGUYEN, LA WALKER, ID DEFIGUEIREDO, RJP Rice Univ. (United States) Univ. of California/Irvine (United States)

ISBN: (纸本)0819404543

The use of kinematic redundancy in control algorithms to avoid singularities evade obstacles minimize joint torques manipulator kinetic energy end effector contact forces etc. . . has been among the most active research topics in the field of robotics in the past few years. However these approaches have been associated mainly with rigid manipulators where there is no unpredictable flexible motions. When dealing with flexible manipulators the flexibility of the system will cause undesired inaccuracy in end effector motion. If these manipulators are kinematically redundant their kinematic redundancy can be used to compensate for the end effector motion inaccuracy and in many cases help damp out the vibrations. This paper examines this issue and introduces new control algorithms designed to regulate the flexibility while maintaining precise tracking of the end effector trajectory. The dynamic model used is a special case of the general multi-body dynamics designed to maximize its computational efficiency.

关键词： Robotics Space robots Control systems Kinematics Fourier transforms Motion controllers Computer simulations Numerical simulations detection and tracking algorithms Motion models

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Computer-assisted esophageal wall motion analysis from digital fluoroscopic images

Computer-assisted esophageal wall motion analysis from digit...

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Medical Imaging 2000 Conference

作者： Senoo, A Shimada, M Ito, A Yagi, K Ogura, I Negishi, T Katoh, T Matsumoto, M Yoshikawa, K Tokyo Metropolitan Univ Hlth Sci Dept Radiol Technol Tokyo Japan

ISBN: (纸本)0819435953

The dynamic image recognition is applied to the robot engineering sciences. This technology (the optical flow method) was used the computer aided diagnosis of the esophageal fluoroscopy. The dynamic images were obtained by means of using digital video recorder. The motion vectors are calculated using the computer vision algorithm (the gradient based method) from these dynamic images in each pixels. The motion vectors were visualized in color images and allow images. The results showed that the motion of normal esophageal walls were mainly in the horizontal direction, whereas a large oblique direction component was observed in that of abnormal esophageal walls. The dynamic image recognition was useful in clinical study for the analysis of esophageal wall motion.

关键词： Esophagus detection and tracking algorithms Motion analysis Calculus Optical flow Tumors Barium Fluoroscopy Diagnostics Visualization

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Spatial filtering for clutter rejection in (moving) point-target detection

Spatial filtering for clutter rejection in (moving) point-ta...

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Imaging Spectroscopy I 1980

作者： Fried, David L. Optical Sciences Company PlacentiaCA92670 United States

In carrying out a fairly extensive amount of analysis of the expected performance of various types of signal processing schemes for detection of point targets with a mosaic sensor, we have observed that moving target detection in a cluttered background is so effectively accomplished by an MTI processor that there is virtually no additional help to be obtained from a spatial filtering processor. This does mean that in all cases tharget detection is assured by MTI signal processing methods. The target strength may be so low, or the clutter level so high that nothing can be done that will result in an adequate signal-to-clutter ratio. But in any case, what we have found is that the signal-to-clutter ratio obtained with MTI signal processing alone is much higher than the signal-to-clutter ratio obtained with spatial filtering alone, and that the combination of spatial filtering with MTI signal processing yields a signal-to-clutter ratio that is not noticeably better than that obtained with MTI signal processing alone. In the following we shall try to present an analytical basis for understanding why this is the case.

关键词： Signal processing Sensors Spatial filters Target detection Signal detection Image sensors Imaging spectroscopy Spatial frequencies Optical components detection and tracking algorithms

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MPPT control technology based on improved variable step conductance increment

MPPT control technology based on improved variable step cond...

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2024 International Conference on Automation and Intelligent Technology, ICAIT 2024

作者： Li, Zhenling Gao, Yukun CGN New Energy Holdings Co. Ltd Beijing China

ISBN: (数字)9781510685819

ISBN: (纸本)9781510685802

In order to solve the shortcomings of the traditional constant step incremental conductance method in both speed and accuracy, an improved variable step incremental conductance method is proposed. The simulation results show that compared with the traditional constant step conductance increment method, the new MPPT (maximum power point tracking) control method shows faster convergence speed and higher convergence accuracy, and effectively overcomes the limitation of the traditional method in processing optimization speed and accuracy. © The Authors.

关键词： Solar cells Mathematical optimization Photovoltaics Optical power tracking algorithms detection and tracking algorithms Image segmentation Diodes Batteries Shadows Solar energy

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Word recognition using ideal word patterns

Word recognition using ideal word patterns

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Document Recognition

作者： Zhao, Xin Srihari, Sargur N. SUNY/Buffalo (United States)

ISBN: (纸本)081941476X

The word shape analysis approach to text recognition is motivated by discoveries in psychological studies of the human reading process. It attempts to describe and compare the shape of the word as a whole object without trying to segment and recognize the individual characters, so it bypasses the errors committed in character segmentation and classification. However, the large number of classes and large variation and distortion expected in all patterns belonging to the same class make it difficult for conventional, accurate, pattern recognition approaches. A word shape analysis approach using ideal word patterns to overcome the difficulty and improve recognition performance is described in this paper. A special word pattern which characterizes a word class is extracted from different sample patterns of the word class and stored in memory. Recognition of a new word pattern is achieved by comparing it with the special pattern of each word class called ideal word pattern. The process of generating the ideal word pattern of each word class is proposed. The algorithm was tested on a set of machine printed gray scale word images which included a wide range of print types and qualities.

关键词： Shape analysis detection and tracking algorithms Prototyping Distortion Pattern recognition Feature extraction Image quality Image classification Image segmentation Visualization

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OPTIMIZATION OF ART NETWORK WITH BOLTZMANN MACHINE 2

OPTIMIZATION OF ART NETWORK WITH BOLTZMANN MACHINE

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CONF ON SCIENCE OF ARTIFICIAL NEURAL NETWORKS 2

作者： OMIDVAR, OM WILSON, CL Univ. of the District of Columbia (United States) National Institute of Standards and Technology (United States)

ISBN: (纸本)0819412023

Optimization of large neural networks is essential in improving the network speed and generalization power, while at the same time reducing the training error and the network complexity. Boltzmann methods have been used as a statistical method for combinatorial optimization and for the design of learning algorithm. In the networks studied here, the Adaptive Resonance Theory (ART) serves as a connection creation operator and the Boltzmann method serves as a competitive connection annihilation operator. By combining these two methods it is possible to generate small networks that have similar testing and training accuracy and good generalization from small training sets. Our findings demonstrate that for a character recognition problem the number of weights in a fully connected network can be reduced by over 80%. We have applied the Boltzmann criteria to differential pruning of the connections which is based on the weight contents rather than on the number of connections.

关键词： Image processing Neural networks Optical character recognition Optimization (mathematics) Error analysis Network architectures Statistical methods Temperature metrology Artificial neural networks detection and tracking algorithms

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