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检索条件"主题词=detection Algorithms"

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Improved impulse detection in power line communication systems

Improved impulse detection in power line communication syste...

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IEEE International Symposium on Power Line Communications and Its Applications (ISPLC)

作者： Kyoungnam Seo Haniph Latchman Kaywan H. Afkhamie Department Electrical and Computer Engineering University of Florida Gainesville FL USA Intellon Corporation Ocala FL USA

Impulse noise is generated by many house hold appliances that are attached to the electrical network. Its presence is often detrimental to the performance of a power line communication system, causing PHY throughput degradation in the order of 30-50%. The goal of impulse noise mitigation is to improve the SNR of the received signal by means of signal processing tools. In this work we focus on optimizing the detection of impulsive noises. A new method is developed for the setting of the detection threshold, that is both efficiently computed (in an iterative manner), and performs well in various impulsive noise conditions. Once impulses are detected they are removed from the received waveform by applying simple windowing mechanisms. To evaluate different impulse detection algorithms we test them against real life (impulsive) noise waveforms that have been captured on the power line. The selected algorithm is further validated on the power line against realtime captures of impulse noise impeded signals.

关键词： Power line communications Signal processing Noise generators Home appliances Physical layer Throughput Degradation Signal to noise ratio Iterative methods detection algorithms

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Discrimination of Insoluble-Carbohydrate Binding Proteins and Their Binding Sites Using a 3D Motif detection Method

Discrimination of Insoluble-Carbohydrate Binding Proteins an...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Andrew C. Doxey Zhenyu Cheng Brendan J. McConkey Department of Biology University of Waterloo Waterloo ONT Canada

We apply a 3D motif detection approach to insoluble-carbohydrate binding modules (CBMs), a class of proteins that share a common binding activity but lack a common sequence motif or fold. Key features of insoluble-carbohydrate binding sites were incorporated into a 3D motif detection algorithm, and used in a linear discriminant analysis. Our method effectively discriminated all known type A CBMs from a non-redundant structural dataset and correctly detected known binding sites without any false positives. The algorithm was used to screen a structural database of homology-modeled proteins from tobacco, and the results were experimentally validated using an affinity purification assay and mass spectrometric protein identification. The algorithm correctly predicted CBMs and binding sites not included in the training set, and predicted a previously unknown binding site in the PR-5d protein family. This work highlights the potential of 3D motif detection methods for use in large-scale functional annotation.

关键词： Proteins Amino acids Bioinformatics detection algorithms Sequences Databases Purification Mass spectroscopy Prediction algorithms Crystallization

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A Method for Fast Shot Boundary detection Based on SVM

A Method for Fast Shot Boundary Detection Based on SVM

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Congress on Image and Signal Processing, CISP

作者： Xue Ling Ouyang Yuanxin Li Huan Xiong Zhang Beihang University Beijing China

An algorithm for fast shot boundary detection based on SVM (Support Vector Machine) is proposed. In this algorithm, smooth intervals inside shots are first eliminated from the original video frame sequence. During this process, a gray variance sequence is extracted and serves as the basis for the detection of smooth intervals. Then a new frame sequence named RFS (Reordered Frame Sequence) is formed. Video features such as intensity pixel-wise difference, color histogram differences in HSV space and edge histogram differences in X and Y direction are extracted from RFS. These features are presented as input vectors to the SVM to implement the cut detection. After the cut detection, temporal multi-resolution is applied to frames in RFS to fulfill the gradual change detection. Experimental results show that the proposed algorithm can implement the real-time shot boundary detection, while guarantee the performance.

关键词： Gunshot detection systems Support vector machines Histograms Signal processing algorithms Video sequences Change detection algorithms Video compression detection algorithms Signal resolution Displays

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Depth-of-interaction detection and correction with a multi-scale algorithm in CCD based gamma cameras

Depth-of-interaction detection and correction with a multi-s...

引用

IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Marc A. N. Korevaar Jan W. T. Heemskerk Marlies C. Goorden Freek J. Beekman Section of Radiation Detection and Matter Department of R3 Applied Science Delft University of Technnology Delft Netherlands Department of Nuclear Medicine Image Sciences Institute University Medical Centre Utrecht Netherlands

Gamma cameras based on Charge Coupled Devices (CCDs) and micro-columnar CsI scintillators can reach high spatial resolutions. However, the gamma interaction probability of these scintillators is low (typically ≪30% at 141 keV) due to the limited thickness of presently available micro-columnar scintillators. Continuous scintillators can improve the interaction probability but suffer from increased light spread compared to columnar scintillators. In addition, for both types of scintillators gamma photons incident at an oblique angle reduce the spatial resolution due to the variable depth of interaction (DOI). To improve spatial resolution and spectral characteristics of these detectors, we have developed a fast analytic scintillation detection algorithm that makes use of a depth-dependent light spread model and as a result is able to determine the DOI in the scintillator. This algorithm, performing multi-scale frame analysis, was tested for an Electron Multiplying CCD (EM-CCD) optically coupled to CsI(Tl) scintillators of different thicknesses. For a 2.6 mm thick scintillator a spatial resolution of 148 μm Full Width Half Maximum (FWHM) was obtained with an energy resolution of 46% FWHM for gamma photons incident perpendicularly (interaction probability 61% at 141 keV). The multi-scale algorithm improves the spatial resolution up to 11 %, and the energy resolution up to 36 % compared to a previously implemented algorithm that did not model the depth-dependent light spread. In addition, the multi-scale algorithm can accurately approximate DOI. As a result, degradation of the spatial resolution due to the variable DOI for gamma photons incident at a 47° angle was improved from 2600 μm to 508 μm FWHM for a 3 mm thick scintillator. We conclude that the multi-scale algorithm significantly improves CCD based gamma cameras as can be applied in future SPECT systems.

关键词： Gamma ray detection Gamma ray detectors Charge coupled devices Charge-coupled image sensors Spatial resolution Single photon emission computed tomography Algorithm design and analysis Energy resolution Solid scintillation detectors detection algorithms

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Radarsat-2 Moving Object detection Experiment (MODEX)

Radarsat-2 Moving Object Detection Experiment (MODEX)

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Shen Chiu Chuck Livingstone Ishuwa Sikaneta Christoph Gierull Pete Beaulne Radar Systems Section Defence Research and Development Canada Ottawa ONT Canada

This paper presents an overview of various detection and estimation algorithms that have been implemented in the RADARSAT-2 MODEX Processor as well as experimental plans for the validation and demonstration of the spa... 详细信息

关键词： Object detection Detectors Filter bank Parameter estimation Histograms Phase estimation Radar detection Synthetic aperture radar detection algorithms Research and development

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Automated Facial Feature detection from Portrait and Range Images

Automated Facial Feature Detection from Portrait and Range I...

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IEEE Southwest Symposium on Image Analysis and Interpretation

作者： Sina Jahanbin Alan C. Bovik Hyohoon Choi Department of Electrical and Computer Engineering University of Texas Austin USA Computer Vision Research Laboratory Sealed Air Corporation San Jose USA

ISBN: (纸本)9781424422968;1424422965

We propose a novel technique to detect feature points from portrait and range representations of the face. In this technique, the appearance of each feature point is encoded using a set of Gabor wavelet responses extracted at multiple orientations and spatial frequencies. A vector of Gabor coefficients, called a jet, is computed at each pixel in the search window on a fiducial and compared with a set of jets, called a bunch, collected from a set of training data on the same type of fiducial. The desired feature point is located at the pixel whose jet is the most similar to the training bunch. This is the first time that Gabor wavelet responses were used to detect facial landmarks from range images. This method was tested on 1146 pairs of range and portrait images and high detection accuracies are achieved using a small number of training images. It is shown that co-localization using Gabor jets on range and portrait images resulted in better accuracy than using any single image modality. The obtained accuracies are competitive to that of other techniques in the literature.

关键词： Facial features Face detection Computer vision Face recognition Shape Nose Active appearance model Data mining Robustness detection algorithms

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An accurate algorithm for head detection based on XYZ and HSV hair and skin color models

An accurate algorithm for head detection based on XYZ and HS...

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IEEE International Conference on Image Processing

作者： Zui Zhang Hatice Gunes Massimo Piccardi Faculty of Information Technology University of Technology Sydney Australia

Head detection in images and videos plays an important role in a wide range of computer vision and multimedia applications. In this paper, we propose a new head detection algorithm that is capable of handling significantly variable conditions in terms of viewpoint (i.e. frontal, profile, back view, from -180 degrees to +180 degrees), tilt angle (i.e. from horizontal to aerial), scale and resolution. To this aim, we built a new model for the head based on appearance distributions and shape constraints. The appearance distribution models the colors of hair and skin by sets of Gaussian mixtures in the XYZ and HSV color spaces. The shape constraint fits an elliptical model to the candidate region and compares its parameters with priors based on the human anatomy. This presents a pixel-level measurement of accuracy for the proposed algorithm both prior and after applying the spatial constraints referenced by the elliptical model. The excellent accuracy at both levels confirms the accuracy of the appearance model and the appropriateness of the spatial and topological process.

关键词： Hair Skin Head Face detection Colored noise Humans Videos Application software Shape detection algorithms

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A nonlinear kernel-based joint fusion/detection of anomalies using Hyperspectral and SAR imagery

A nonlinear kernel-based joint fusion/detection of anomalies...

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IEEE International Conference on Image Processing

作者： Nasser M. Nasrabadi US Army Research Laboratory Adelphi MD USA

In this paper a new nonlinear joint fusion and detection algorithm is proposed for locating anomalies from two different types of sensor data (synthetic aperture radar (SAR) and hyperspectral sensor (HS) data). The proposed approach jointly exploits the nonlinear correlation or dependencies between the two sensors in order to simultaneously fuse and detect the objects of interest (mines). A well-known anomaly detector, so called RX algorithm is extended to perform fusion and detection simultaneously at the pixel level by appropriately concatenating the information from the two sensors. This approach is then extended to its nonlinear version using the idea of kernel learning which explicitly exploits the higher order dependencies (nonlinear correlations) between the two sensor data through an appropriate kernel.

关键词： Hyperspectral imaging Radar detection Hyperspectral sensors Sensor fusion Kernel detection algorithms Synthetic aperture radar Fuses Object detection Detectors

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Extending the RX anomaly detection algorithm to continuous spectral and spatial domains

Extending the RX anomaly detection algorithm to continuous s...

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IEEE Southeastcon

作者： Alan M. Thomas Georgia Institute of Technology USA

The RX anomaly detection algorithm is a statistical method for detecting pixels in hyperspectral imagery that are significantly different from the other pixels in their locale. The RX algorithm is based upon the assumption of an existing uniform discrete sampling in both space and spectrum. In this report, we give consideration to extending the RX algorithm to continuous spatial and spectral domains so that future optical devices may be optimally constructed for anomaly detection. This report gives a heuristic outline for the extension of the RX algorithm to continuous spatial and spectral domains, explores new concepts in functional statistics necessary to make the algorithm rigorous, and suggests directions for the continuation of this research in the future.

关键词： detection algorithms Hyperspectral imaging Pixel Hyperspectral sensors Statistics Space technology Sampling methods Landmine detection Statistical analysis Image sampling

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Design and test of a long-term fall detection system incorporated into a custom vest for the elderly

Design and test of a long-term fall detection system incorpo...

引用

IET Irish Signals and Systems Conference (ISSC 2008)

作者： Alan K. Bourke Pepijn W.J. van de Ven Amy Chaya Gearoid OLaighin John Nelson Department of Electronic and Computer Engineering University of Limerick Limerick Ireland Department of Electronic Engineering National University of Ireland Galway Ireland

ISBN: (纸本)9780863419317

Falls in the elderly are a major problem for society. A serious consequence of falling is the "long-lie". A fall detection system and algorithm, incorporated into a custom designed garment has been developed which will automatically detect falls and potentially reduce the incidence of the "long-lie". The developed fall detection system consists of a tri-axial accelerometer, microcontroller, battery and Bluetooth module. This sensor is attached to a custom designed vest, designed to be worn by the elderly person under clothing. The fall detection algorithm was developed and incorporates both impact and posture detection capability. The vest was developed using feedback from elderly subjects donning, wearing and doffing a prototype vests and subsequently filling in a questionnaire. The re-designed vest and fall algorithm was tested in two clinical trials. Trial 1: young healthy subjects performing normal activities of daily living (ADL) and falls onto crash mats, while wearing the vest and sensor. Trial 2: The system was subsequently tested using 10 elderly subjects wearing the system over the course of 4 weeks, for 8 hours a day. Two teams of 5 elderly subjects wore the sensor system in turn for 2 week each. Results from trial 1, show that falls can be distinguished from normal activities with a sensitivity >90% and a specificity of >99%, from a total data set of 264 falls and 165 normal ADL. In trial 2, over 833 hours of monitoring was performed over the course of the four weeks from the elderly subjects, during normal daily activity. In this time no actual falls were recorded, however the system registered a total of the 42 fall-alerts. Further development of the system will include a more accurate fall-detection algorithm, more comfortable sensor attachment method, lighter and smaller sensor as well as, mobility monitoring and energy expenditure measurement. A fall detection system incorporated into a custom designed garment has been developed which will hel

关键词： Long-term fall-detection Accelerometer Bluetooth Elderly aged person falls vest Fall Bluetooth detection systems accelerometers Accidental Falls detection algorithms Custom design Sensor systems Elderly fall Activities of Daily Living

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