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检索条件"主题词=Detection Algorithms"

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A robust front page detection algorithm for large periodical collections

A robust front page detection algorithm for large periodical...

引用

International Conference on Pattern Recognition

作者： Iuliu Konya Christoph Seibert Sebastian Glahn Stefan Eickeler Fraunhofer Institute for Intelligent Analysis and Information Systems Sankt Augustin Germany

Large-scale digitization projects aimed at periodicals often have as input streams of completely unlabeled document images. In such situations, the results produced by the automatic segmentation of the document stream into issues heavily influence the overall output quality of a document image analysis system. As a solution to the issue segmentation problem, this paper introduces a robust, two-step front page detection algorithm. First, the salient connected components from the front page of the periodical are described using a multi-dimensional Gaussian distribution based on discrete cosine transform (DCT) features. Second, a graph model is computed by applying Delaunay triangulation on the selected set of components. A specialized, error-tolerant graph matching algorithm is used to compute the distance score between the model and each candidate page. Experiments on a large, real-world newspaper data set demonstrate the generality and effectiveness of the proposed method.

关键词： Robustness detection algorithms Pattern recognition Image analysis Text analysis Gaussian distribution Streaming media Image segmentation Discrete cosine transforms Shape

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Polynomial-complexity maximum-likelihood block noncoherent MPSK detection

Polynomial-complexity maximum-likelihood block noncoherent M...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Dimitris S. Papailiopoulos George N. Karystinos Department of Electronic and Computer Engineering Technical University of Crete Chania Greece

In wireless channels, maximum-likelihood (ML) block noncoherent detection offers significant gains over conventional symbol- by-symbol detection when the fading channel coefficients are not available and cannot be estimated at the receiver. Certainly, in general the complexity of the block detector grows exponentially with the symbol sequence length. However, it has been recently shown that for M-ary phase-shift keying (MPSK) modulation block noncoherent detection can be performed with polynomial complexity. In this work, we develop a new ML block noncoherent detector for MPSK transmission of arbitrary order and multiple-antenna reception. The proposed algorithm introduces auxiliary spherical variables and constructs with polynomial complexity a polynomial- size set which includes the ML data sequence. It is shown that the complexity of the proposed algorithm is polynomial in the sequence length and at least one order of magnitude lower than the complexity of computational-geometry based noncoherent detection algorithms that have been developed recently.

关键词： Polynomials Maximum likelihood detection Maximum likelihood estimation Fading Detectors Phase shift keying detection algorithms Channel estimation Character generation Phase modulation

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Harmonic detection Algorithm Based on Recursive Filter

Harmonic Detection Algorithm Based on Recursive Filter

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11th International Conference on Electrical Machines and Systems(第11届国际电机与系统会议)

作者： Guozhi Chen Longdao Chen Zhongfa Cai Zhejiang University /College of Electrical Engineering Department Hangzhou 310027 China

Due to the problems of Fourier algorithm and wavelet algorithm on harmonic detection, proposed harmonic detection algorithm based on a recursive filter in this paper. Unlike a wavelet, the central frequency and frequency window radius of the recursive filter can be adjusted separately, the magnitude frequency property (MFP) of its real part and imaginary part is identical, symmetrical and no side lobes, moreover has no relative to the central frequency. By virtue of these attributes, it can overcome frequency spectrum leakage and fence effect of FFT, eliminate frequency bank aliasing of wavelet transform, and realize accurately detection of harmonic and interharmonic in power system. Further, a recursive algorithm is adopted that updates current output only using several previous sample values and filtering outputs. Thus, this recursive algorithm is highly desirable for real-time applications. The simulation results show that the method is able to identify numbers of harmonic and interharmonic accurately, and has highly detecting accuracy to amplitude and frequency.

关键词： Power harmonic filters detection algorithms Power system harmonics Frequency Discrete Fourier transforms Band pass filters Power system simulation Fourier transforms Wavelet transforms Leak detection

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Battery Chemistry detection Algorithm Implementable with Intelligent Systems: A Step towards the Development of a Novel Charger Applicable for Multi-Chemistry Environment

Battery Chemistry Detection Algorithm Implementable with Int...

引用

International Symposium on Intelligent Information Technology Application, IITA

作者： Raisul Islam Sarkar Rahat Mohammad Anwar Ahmed Tashrif Kamal Samia Nawar Rahman Hasan Mohammad Faraby Hafiz Imtiaz Mohammed Shahriar Jahan Fahmida Shaheen Tulip Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh Department of Electrical and Electronic Engineering United International University Dhaka Bangladesh

This paper introduces a theory for the development of a fully automated multiple chemistry battery charger. This can be possible through the detection of battery chemistry. The paper presents an algorithm to differentiate between Ni based, Li-ion and Sealed Lead Acid (SLA) batteries through the analysis of voltage profile during charging and discharging periods. The algorithm was implemented and tested in an intelligent charger capable of charging aforementioned types of batteries without any prior identification of battery type from the user. This industrially viable solution for developing multiple chemistry charger can easily be incorporated in any embedded system using minimum input and circuit arrangement connected to the battery.

关键词： Batteries Chemistry detection algorithms Intelligent systems Voltage Circuits DH-HEMTs Phase locked loops Information technology Chemical technology

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Back-Propagation Neural Network for Traffic Incident detection Based on Fusion of Loop Detector and Probe Vehicle Data

Back-Propagation Neural Network for Traffic Incident Detecti...

引用

International Conference on Natural Computation (ICNC)

作者： Liu Yu Lei Yu Jianquan Wang Yi Qi Huimin Wen School of Traffic and Transportation Beijing Jiaotong University Beijing P.R. China Department of Transportation Studies Texas Southern University Houston Texas U.S.A Beijing Transportation Research Center Beijing China Beijing Transportation Research Center Beijing P.R. China

Traffic incident detection based on a fusion of various available data sources has been an evolving research topic in ITS. This paper proposes a data fusion model for traffic incident detection using BP neural network. In this model, the cumulative sum (CUSUM) approach is used to develop incident detection algorithms using loop detector data and probe vehicle data respectively, while the BP neural network combines the outputs from both incident detection algorithms. The proposed algorithm is tested and evaluated with the data generated by the simulation model INTEGRATION. The result shows that the outputs using BP neural network improves the accuracy provided by each single source incident detection algorithm.

关键词： Vehicle detection Neural networks Telecommunication traffic Detectors Probes Traffic control Vehicles detection algorithms Artificial neural networks Transportation

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A Peak-Trough detection Algorithm Based on Momentum

A Peak-Trough Detection Algorithm Based on Momentum

引用

Congress on Image and Signal Processing, CISP

作者： K. Harmer G. Howells W. Sheng M. Fairhurst F. Deravi Department of Electronics University of Kent Canterbury Kent UK

This paper presents a simple, yet novel, approach to peak-trough detection using a rudimentary model of Newtonian mechanics. Based on the line-searching technique also employed in artificial neural network technology to determine global minima, the momentum is used to find both peaks and troughs of a signal. This algorithm provides a fast alternative to the traditional techniques, which uses contextual information in order to determine prominent peaks and troughs without requiring smoothing or thresholding.

关键词： detection algorithms Signal processing algorithms Shape Noise robustness Change detection algorithms Neural networks Friction Gravity Artificial neural networks Smoothing methods

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detection of DoS and DDoS attacks in NGMN using frequency domain analysis

Detection of DoS and DDoS attacks in NGMN using frequency do...

引用

Asia-Pacific Conference on Communications

作者： Fazirulhisyam Hashim M. Rubaiyat Kibria Abbas Jamalipour University of Sydney NSW Australia

Ensuring security of the infrastructure against external attacks across network boundaries constitutes one of primary attributes as well as challenges of the next generation mobile network (NGMN). To allay the possibility of such attacks emancipating the NGMN architecture, it is necessary to identify the attack types. However, detection of the attack types from various traffic flows (as is the case in network links) and their subsequent classification can be a very daunting task, especially when both the attack and the legitimate traffic exhibit similar statistical properties (such as denial-of-service (DoS) and distributed DoS (DDoS)). Furthermore, the attackerpsilas ability to spoof and forge the packet header information (including IP address) makes the detection process even more difficult. Conventional anomaly based attack detection mechanisms have been found wanting in such situations. In an attempt to provide a solution, this paper proposes a detection algorithm that identifies and characterizes network traffic by investigating the frequency spectrum distribution. The Lomb periodogram is utilized to determine the power spectrum of the observed traffic whereupon two deviation score parameters are employed to segregate the anomaly traffic flows from legitimate ones in a two-step method. For simplicity purposes, the efficiency of such classification effort is demonstrated for DoS and DDoS attacks only (for their statistical similarity to normal traffic).

关键词： Computer crime Frequency domain analysis Telecommunication traffic Data security Australia Intrusion detection Next generation networking Monitoring detection algorithms Distributed databases

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Knee Point detection on Bayesian Information Criterion

Knee Point Detection on Bayesian Information Criterion

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Qinpei Zhao Mantao Xu Pasi Fränti Speech & Image Processing Unit Department of Computer Science University of Joensuu Joensuu Finland

The main challenge of cluster analysis is that the number of clusters or the number of model parameters is seldom known, and it must therefore be determined before clustering. Bayesian information criterion (BIC) often serves as a statistical criterion for model selection, which can also be used in solving model-based clustering problems, in particular for determining the number of clusters. Conventionally, a correct number of clusters can be identified as the first decisive local maximum of BIC; however, this is intractable due to the overtraining problem and inefficiency of clustering algorithms. To circumvent this limitation, we proposed a novel method for identifying the number of clusters by detecting the knee point of the resulting BIC curve instead. Experiments demonstrated that the proposed method is able to detect the correct number of clusters more robustly and accurately than the conventional approach.

关键词： Knee Bayesian methods Clustering algorithms detection algorithms Speech analysis Parameter estimation Artificial intelligence Speech processing Image processing Computer science

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Parallel detection algorithm using multiple QR decompositions with permuted channel matrix for SDM/OFDM

Parallel detection algorithm using multiple QR decomposition...

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International Symposium on Wireless Pervasive Computing (ISWPC)

作者： Chang-Jun Ahn Faculty of Information Sciences Hiroshima City University Hiroshima Japan

SDM/OFDM systems transmit different data using the same frequency, so it is necessary to separate simultaneously received signals in the receiver. Previous studies have shown that maximum likelihood detection (MLD) provides the best BER performance. However, the complexity of MLD exponentially increases with the constellation size and the number of transmit antenna branches. Therefore, it is impractical to use a full MLD without reducing its computational complexity, because it would be prohibitively large for implementation. Recently, the use of QRD-M has been proposed for reducing the system complexity, while maintaining the performance of the system. However, the QRD-M performance depends on the number of surviving symbol replica candidates. When QRD-M is used with a small number of surviving symbol replica candidates, the performance declines, but when there is a large number of surviving symbol replica candidates and the transmitter antenna branches, QRD-M requires a large memory to maintain their branch metrics, and long latency time is also required. To reduce these problems, in this paper, we propose a parallel detection algorithm using multiple QR decompositions with permuted channel matrices for SDM/OFDM systems.

关键词： detection algorithms Matrix decomposition OFDM Transmitting antennas Transmitters Receiving antennas Antennas and propagation Maximum likelihood detection Bit error rate Computational complexity

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Anomaly detection in multi-polarimetric radar images

Anomaly detection in multi-polarimetric radar images

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IEEE Convention of the Electrical and ELectronic Engineers in Israel

作者： Georgy Melamed Stanley R. Rotman Dan G. Blumberg Anthony J. Weiss Department Electrical Engineering Tel-Aviv University Israel Department Electrical and Computer Engineering Ben-Gurion University of the Negev Beersheba Israel Department Geography and Environmental Development Ben-Gurion University of the Negev Beersheba Israel

An anomaly detection algorithm for SAR (synthetic aperture radar) images, making use of multi-polarized data, is developed. The processing contains several stages including: calibration of the images, information parameters extraction and speckle filtering, suspect pixels detection and morphology operator application. The developed algorithm is independent of the anomaly radar cross section; it depends only on the physical structure. The proposed processing is non-iterative, adaptive and automatic. Performance evaluation shows improved performance of the algorithm over the common alternatives.

关键词： Radar detection Radar imaging detection algorithms Synthetic aperture radar Calibration Parameter extraction Speckle Information filtering Information filters Pixel

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