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检索条件"主题词=Detection Algorithms"

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Statistical analysis of RR interval irregularities for detection of atrial fibrillation

Statistical analysis of RR interval irregularities for detec...

引用

Computers in Cardiology (CinC)

作者： A. Ghodrati S. Marinello Draeger Medical Systems Inc. Andover MA USA

We compare two Atrial Fibrillation (AFIB) detection methods from surface ECG, based on RR interval variability in a statistical framework. We obtain the histogram of normalized RR differences for AFIB and non-AFIB episodes using MIT-BIH Arrhythmia database. Two probability density functions (pdf) are employed to model the histograms: Gaussian and Laplace. We then use Neyman-Pearson (NP) detection approach to obtain criteria for AFIB detection. The performance of the two methods is compared using Receiver Operating Curves (ROC) over the different databases. The result shows that the Laplace pdf approximates the histogram of normalized RR differences better than the Gaussian pdf and leads to better AFIB detection performance.

关键词： Statistical analysis Atrial fibrillation Databases Hidden Markov models Histograms Electrocardiography Rail to rail inputs Random variables Patient monitoring detection algorithms

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A novel parallel iterative cycle QR decomposition detection algorithm in VBLAST-OFDM system

A novel parallel iterative cycle QR decomposition detection ...

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IEEE International Symposium on Information (IT) in Medicine and Education, ITME

作者： Yong-jie Li Hong-liang Fu Coll. of Inf. Sci. & Eng. Henan Univ. of Technol. Zhengzhou

A novel parallel iterative cycle QR decomposition detection algorithm in VBLAST-OFDM system is proposed in this paper. In order to overcome the disadvantage of the poor performance of the first detected layer in IQRD algorithm, the parallel detection is applied to the IQRD algorithm and the performance is improved effectively. Simulation results show that the proposed P-IQRD algorithm is superior to the IQRD algorithm.

关键词： detection algorithms Iterative algorithms Transmitting antennas Receiving antennas Frequency-selective fading channels Information science Educational technology OFDM Transmitters Matrix decomposition

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Voice Activity detection Algorithm with Low Signal-to-Noise Ratios Based on Spectrum Entropy

Voice Activity Detection Algorithm with Low Signal-to-Noise ...

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International Symposium on Universal Communication, ISUC

作者： Kun-Ching Wang Yi-Hsing Tasi Department of Information Technology & Communication Shih Chien University Taiwan Information & Communications Research Laboratories Industrial Technology and Research Institute Taiwan

This letter presents a robust voice activity detection (VAD) algorithm for detecting voice activity in noisy environments. The presented robust VAD utilizes the entropy measurement defined in band-splitting spectrum domain to exploit the formant frequency representation as a highly efficient, compact representation of the time-varying characteristics of speech. Additionally, Teager energy operator (TEO) can be employed to provide a better representation of formant information resulting in high performance of classification of speech/non-speech priori to entropy-based measurement. The results show that the proposed algorithm has an overall better performance than the standard ITU-T G.729B VAD and Shen's entropy-based VAD.

关键词： detection algorithms Signal to noise ratio Entropy Speech Acoustic noise Frequency measurement Energy measurement Robustness Frequency estimation Information technology

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An Adaptive Kernel Method for Anomaly detection in Hyperspectral Imagery

An Adaptive Kernel Method for Anomaly Detection in Hyperspec...

引用

International Symposium on Intelligent Information Technology Application, IITA

作者： Feng Mei Chunhui Zhao Hanjun Huo Yan Sun College of Information and Communication Engineering Harbin Engineering of Technology Harbin Heilongjiang China College of Electrical & Information Engineering Heilongjiang Institute of Science and Technology Harbin Heilongjiang China

An adaptive kernel method is proposed for anomaly detection in hyperspectral imagery. The conventional RX anomaly detector suffers from high false alarm rates and low probability of detection due to the assumptions that the local background is Gaussian and homogeneous. Many kernel base anomaly detector are of good nonlinear detection performance, but parameter estimation of the kernel function is difficult for these methods. In this paper, we proposed a adaptive parameter estimation method based on the sum of each spectral band standard deviation for the background clutter pixels and applied it in the kernel RX detector. The kernel function parameters estimation can be obtained along with the shifting of the background clutter pixels automatically so we can avoid a large number of experiments for the parameters determination. Numerical experiments are conducted on real hyperspectral imagery collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Using receiver operating characteristic (ROC) curves, the results show the improved performance and reduction in the false-alarm rate.

关键词： Kernel Hyperspectral imaging Detectors Hyperspectral sensors Parameter estimation detection algorithms Educational institutions Information technology Adaptive signal detection Signal to noise ratio

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Breast contour detection with shape priors

Breast contour detection with shape priors

引用

IEEE International Conference on Image Processing

作者： Ricardo Sousa Jaime S. Cardoso J. F. Pinto da Costa M. J. Cardoso INESC Porto Faculdade de Ciências Universidade do Porto Portugal INESC Porto Faculdade de Engenharia Universidade do Porto Portugal Faculdade de Ciências Universidade do Porto Portugal INESC Porto Faculdade de Medicina Universidade do Porto Portugal

Breast cancer conservative treatment (BCCT) is considered the gold standard of breast cancer treatment. However, aesthetic results are heterogeneous and difficult to evaluate in a standardised way. The limited reproducibility of subjective aesthetic evaluation in BCCT forced the research on objective methods. A recent computer system was developed to objectively and automatically evaluate the aesthetic result of BCCT. In this system, the detection of the breast contour on the digital photograph of the patient is necessary to extract the features subsequently used in the evaluation process. In this paper we extend an algorithm based on the shortest path on a graph to detect automatically the breast contour. The advantage of graph algorithms is that they are guaranteed to find the global optimum of the problem; the difficulty is that they make it hard to enforce shape constraints. We define and compare different techniques to introduce the a priory knowledge of the mammary contour. Experimental results show that the proposed techniques consistently outperform the base method.

关键词： Shape Image edge detection Breast cancer Reproducibility of results Feature extraction Medical treatment Surgery Skin detection algorithms Pixel

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Commentary Paper 1 on "Automatic detection of Adverse Weather Conditions in Traffic Scenes"

Commentary Paper 1 on "Automatic Detection of Adverse Weathe...

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Andrea Prati Di.S.M.I. University of Modena and Reggio Emilia and INFM Reggio Emilia Italy

This paper describes two solutions for detecting snow and fog, respectively, in traffic scenes. The former weather condition is detected by modeling the video luminance with a mixture of Gaussians (MoG), while the lat... 详细信息

关键词： Layout Snow Traffic control Videoconference Surveillance Gaussian processes Harmonic analysis detection algorithms Frequency domain analysis Cameras

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Effect of commuting on the detection and characterization performance of the Bayesian Aerosol Release Detector

Effect of commuting on the detection and characterization pe...

引用

IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)

作者： Aurel Cami Garrick L. Wallstrom William R. Hogan Department of Biomedical Informatics University of Pittsburgh Pittsburgh PA USA

The Bayesian Aerosol Release Detector (BARD) is a system designed to detect and characterize disease outbreaks caused by aerosol releases of B. anthracis. The detection algorithm of BARD requires, among other things, an accurate estimation of the number of spores that would be inhaled under a specific release scenario. This is a challenging problem, in part due to the lack of fine-grained data on the mobility patterns of the exposed population. Indeed, the only type of spatial information routinely contained in biosurveillance databases is the residential administrative unit-such as the home zip code-of each case. The current version of BARD detector deals with this challenge by making the simplifying assumption that exposure to anthrax would occur at onepsilas residential unit. This paper presents an experimental study to assess how BARDpsilas performance would be impacted by incorporation of a commuting model in outbreak simulation. Our results show that incorporation of commuting in simulation leads to statistically and practically significant changes in BARDpsilas detection and characterization performance.

关键词： Bayesian methods Aerosols Detectors Diseases detection algorithms Fungi Spatial databases Data analysis Biomedical informatics Surveillance

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An Improved Fingerprint Singular Point detection Algorithm Based on Continuous Orientation Field

An Improved Fingerprint Singular Point Detection Algorithm B...

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International Symposium on Computer Science and Computational Technology, ISCSCT

作者： Ting Tang Xiaopei Wu Ming Xiang The Key Laboratory of Intelligent Computing & Signal Processing Anhui University Hefei China

It is very important to detect singular points (core and delta) accurately and reliably for classification and matching of fingerprint. In this paper, an improved method for singularity detection in fingerprint images, which based on continuous orientation field, is proposed to improve accuracy of the position and reliability of the singularity. Firstly, the blocks which may contain singularities are detected by computing the Poincare Index. Then, the singularities are detected in the block images. Experiment show that the proposed method can overcome the shortcoming of the traditional method to great extend and is robust to poor quality images.

关键词： Fingerprint recognition detection algorithms Image matching Image segmentation Signal processing algorithms Pixel Gray-scale Computer science Laboratories Computational intelligence

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Improved quality of experience of reconstructed H.264/AVC encoded video sequences through robust pixel domain error detection

Improved quality of experience of reconstructed H.264/AVC en...

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IEEE Workshop on Multimedia Signal Processing

作者： Reuben A. Farrugia Carl J. Debono Department of Communications and Computer Engineering University of Malta Msida Malta

The transmission of H.264/AVC encoded sequences over noisy wireless channels generally adopt the error detection capabilities of the transport protocol to identify and discard corrupted slices. All the macroblocks (MBs) within each corrupted slice are then concealed. This paper presents an algorithm that does not discard the corrupted slices but tries to detect those MBs which provide major visual artefacts and then conceal only these MBs. Results show that the proposed solution, based on a set of image-level features and two support vector machines (SVMs), manages to detect 94.6% of those artefacts. Gains in peak signal-to-noise ratios (PSNR) of up to 5.74 dB have been obtained when compared to the standard H.264/AVC decoder.

关键词： Automatic voltage control Support vector machines Video sequences Decoding Pixel Wireless communication detection algorithms

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A Grouped-Iterative Framework for MIMO detection

A Grouped-Iterative Framework for MIMO Detection

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IEEE Conference on Vehicular Technology (VTC)

作者： Di-You Wu Lan-Da Van Department of Computer Science National Chiao Tung University Hsinchu Taiwan

In this paper, we propose one grouped-iterative framework to generate a family of the MIMO detection algorithms. The presented framework not only includes the conventional iterative, grouped, and Chase detection algorithms, but also derives a new low-complexity MIMO detection algorithm. The proposed detection can adjust some parameters to achieve a range of trade-offs between performance and complexity. In (4,4) system with uncoded 16-QAM inputs, one instance of the proposed detection algorithm not only substantially reduces the multiplication complexity by 26.3% but also outperforms the BODF algorithm about 5 dB. Another instance of the proposed algorithm can save multiplication complexity by 34% at the penalty of 1 dB loss compared with the B-Chase detector.

关键词： Complexity theory detection algorithms MIMO Artificial neural networks Detectors Iterative algorithm Bit error rate

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