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Exposure-focus critical dimension feedback control in 300mm manufacturing technologies

Exposure-focus critical dimension feedback control in 300mm ...

引用

Conference on Advanced Process Control and Automation

作者： Narendra, A Carson, S Morrison, C Intel Corp Hillsboro OR 97124 USA

ISBN: (纸本)0819448494

Control of DCCDs (Develop Check Critical Dimension) is a key aspect of successfully manufacturing semiconductors at Intel. DCCD control was formerly achieved through manual adjustments of the exposure dose on the tool to account for the known effects of non-stationary tool/process drift. An automated application EFCC (Exposure-Focus CD Control) was developed at Intel, to create a robust algorithm and automated implementation, replacing the manual adjustment process. The EFCC algorithm uses DCCD summary measurements as the feedback to the stepper. At the stepper, the exposure setting is adjusted to correct for non-stationary tool/process drift. A weighted average of data from previous lots is used to determine the recommended exposure dose settings. The feedback scheme weights prior lots using a combination of traditional EWMA based weighting and within lot (across sites on wafer) variance based weighting. The EFCC implementation has benefits in increased Cpk, reduced rework, continuous adjustment. Furthermore, as this is an automated control solution, it can be easily extended to support more sophisticated adjustment algorithms.

关键词： Manufacturing Data modeling Process control Process modeling Algorithm development Control systems Feedback control Correlation function detection and tracking algorithms Semiconductor manufacturing

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Into the Wild: A Study in Rendered Synthetic Data and Domain Adaptation Methods 9

Into the Wild: A Study in Rendered Synthetic Data and Domain...

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Conference on Geospatial Informatics IX

作者： Dotter, Marissa Mediavilla, Chelsea Sato, Jonathan Ward, Chris M. Parameswaran, Shibin Harguess, Josh Naval Informat Warfare Ctr 53560 Hull St San Diego CA 92152 USA Shield AI Inc San Diego CA USA NIWC Pacific San Diego CA USA

ISBN: (纸本)9781510626508

Rendering synthetic imagery from gaming engine environments allows us to create data featuring any number of object orientations, conditions, and lighting variations. This capability is particularly useful in classification tasks, where there is an overwhelming lack of labeled data needed to train state-of-the-art machine learning algorithms. However, the use of synthetic data is not without limit: in the case of imagery, training a deep learning model on purely synthetic data typically yields poor results when applied to real world imagery. Previous work shows that "domain adaptation", mixing real-world and synthetic data, improves performance on a target dataset. In this paper, we train a deep neural network with synthetic imagery, including balls, cars, and overhead ship imagery, and investigate a variety of methods to adapt our model to corresponding datasets of real images.

关键词： Image classification Data modeling detection and tracking algorithms Image quality Statistical analysis Visualization Earth observing sensors Neural networks Satellite imaging Satellites

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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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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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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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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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Adaptive clutter suppression for ground penetrating radar

Adaptive clutter suppression for ground penetrating radar

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Conference on detection and Remediation Technologies for Mines and Minelike Targets X

作者： Carhoun, DO Engn Technol Inc Orlando FL 32826 USA

ISBN: (纸本)0819457795

Adaptive methods are currently in use for GPR to detect shallow-buried targets in the presence of ground-bounce that may be orders of magnitude greater than the target response. One such method that has been used with noteworthy success to reduce the soil background has been called the Principal Components Algorithm (PCA) that applies the Mahalanobis distance measure, a quadratic form, to distinguish the energy in a target from the background energy. We discuss an alternative vector subspace discrimination method borrowed from adaptive spatial filtering that has been used successfully for suppressing Doppler-spread ionospheric clutter in a high frequency radar application [4,5]. This method first estimates the background vector subspace containing the clutter during a training phase and then projects the current response on the orthogonal complement of the estimated subspace to extract the desired signal during the search phase. Discrete clutter in the output response is reduced without attenuating the target signal by applying constraints derived from the estimated target eigenstructure, either measured or modeled. Mathematical details of the algorithm are presented in an appendix. Comparison of results of the PCA and vector subspace projection methods applied to a stepped-frequency GPR have shown the performance of the proposed algorithm to be better in terms of clutter suppression and principal component economy while also retaining the phase and amplitude of the signal samples to facilitate array processing useful for forward looking ground penetrating radar.

关键词： General packet radio service Principal component analysis Receivers detection and tracking algorithms Target detection Phased arrays Ground penetrating radar Data fusion Land mines Sensors

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