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检索条件"主题词=detection algorithms"

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AnomBench: A Benchmark for Volume-Based Internet Anomaly detection

AnomBench: A Benchmark for Volume-Based Internet Anomaly Det...

引用

GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference

作者： Shashank Shanbhag Tilman Wolf Department of Electrical and Computer Engineering University of Massachusetts Amherst MA USA

Developing algorithms to detect anomalies in network traffic is an important goal to achieve secure and efficient operation of the Internet. To evaluate different algorithms, it is crucial to have a set of standardized test cases. We propose a benchmark suite called "AnomBench" that consists of sixteen different traffic scenarios that contain various different traffic anomalies. We describe why these scenarios are representative and show the results of a prototype implementation on DETERlab.

关键词： Internet Telecommunication traffic detection algorithms Prototypes Traffic control IP networks Benchmark testing Intrusion detection Machine learning Bandwidth

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Partial detection for multiple antenna cooperation

Partial detection for multiple antenna cooperation

引用

Annual Conference on Information Sciences and Systems (CISS)

作者： Kiarash Amiri Joseph R. Cavallaro Center of Multimedia Communication Department of Electrical and Computer Engineering Rice University Houston TX USA

Multi-antenna relays can significantly increase the speed and reliability of wireless systems. However, because of the complexity of MIMO detection, there is considerable overhead in implementing a MIMO relay if the conventional detect-and-forward strategy is used. To address this challenge, we propose a novel cooperative partial detection (CPD) strategy that partitions the detection task between the relay and the destination. CPD leverages the structure of the tree-based close-to-ML MIMO detectors, and modifies the tree traversal so that instead of visiting all the levels of the tree, only a subset of the levels, thus a subset of the transmitted streams, are visited. This novel approach reduces the tree levels, i.e. dimensions, in both the relay and the destination. Moreover, CPD provides a flexible method to control the level of partitioning between the relay and the destination, and thus, adjust the detection computational complexity in the relay and the destination. Monte-Carlo simulation results show that, under equal transmit power and complexity constraint in the destination, CPD achieves a better BER performance compared to the non-relay scenario, with limited computational overhead in the relay.

关键词： Relays MIMO Detectors Computational complexity Power system relaying Decoding detection algorithms Multimedia communication Multimedia systems Bit error rate

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Fabric Defect detection Based on Adaptive Local Binary Patterns

Fabric Defect Detection Based on Adaptive Local Binary Patte...

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2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

作者： Rong Fu Meihong Shi Hongli Wei Huijuan Chen School of Computer Science Xi'an Polytechnic University School of Electronic EngineeringXidian Univ School of Computer Science Xi'an Polytechnic UniversityXi'an China School of Electronic Information Engineering Xi'an Technological UniversityXi'an China School of Computer Science Xi'an Polytechnic University

ISBN: (纸本)9781424447749

Adaptive local binary patterns method is proposed in this paper, on which an effective fabric defect detection algorithm is designed. ALBP method selects the frequently occurred patterns to construct the main pattern set, which avoids using the same pattern set to describe different texture structures in uniform local binary patterns method. The features of free defect image are extracted according to the set and the threshold is confirmed. The image to be tested is divided into same size detection windows from which ALBP features are also extracted. Defective window is found through comparing ALBP features with threshold. The experiment exhibited the detection effect of the proposed method is comparatively better than traditional LBP method from human visual aspect and detection accuracy.

关键词： fabric defect defect image Defect detection detection algorithms Binary Self tuning texture structure windows windows

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Robust voice activity detection algorithm using spectrum estimation and dynamic thresholding

Robust voice activity detection algorithm using spectrum est...

引用

IEEE Latin-American Conference on Communications, LATINCOM

作者： Efrain Zenteno Manuel Sotomayor Telecommunications Engineering Universidad Católica San Pablo Arequipa Peru

An algorithm for voice activity detection (VAD) is presented in this paper, it uses the classical short time Fourier transform (STFT) followed by dynamic thresholding over the noise floor which allows accurate determination for voiced/unvoiced frame. This algorithm has also been implemented in a DSP plataform to evaluate its performance in real time, where results have shown that such method presents accurate voiced/unvoiced determination under unknown signal to noise ratio (SNR) conditions.

关键词： Robustness detection algorithms Spectral analysis Frequency Speech analysis Fourier transforms Signal to noise ratio Speech processing Spectrogram Speech enhancement

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The detection of Frequency Hopping Signal Using Compressive Sensing

The Detection of Frequency Hopping Signal Using Compressive ...

引用

International Conference on Information Engineering and Computer Science (ICIECS)

作者： Jia Yuan Pengwu Tian Hongyi Yu Department of Communication Engineering I.T. Institute of Zhengzhou Zhengzhou China

Compressive sensing (CS) creates a new framework of signal reconstruction from a smaller set of incoherent projection compared with the traditional Nyquist-rate sampling theory. Recently, it has been shown that CS can solve some signal processing problems given incoherent measurements without reconstructing signals. Moreover, the number of measurements for most compressive signal processing application such as detection, estimation and classification is lower than that necessary for signal reconstruction. Based on CS, this paper presents a novel detection algorithm of frequency hopping (FH) signals. Given the hop interval, the FH signals can be identified and the hopping frequencies can be estimated with a tiny number of measurements. Simulation results demonstrate that the method is effective and efficient.

关键词： Signal processing Frequency estimation Cities and towns Spread spectrum communication Signal reconstruction Signal processing algorithms detection algorithms Signal sampling Frequency measurement Security

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An Adaptive Algorithm for Harris Corner detection

An Adaptive Algorithm for Harris Corner Detection

引用

International Conference on Computational Intelligence and Software Engineering (CiSE)

作者： Zhiyong Ye Yijian Pei Jihong Shi School of Information Yunnan University Kunming China

Corner points are interesting as they are formed from two or more edges and edges usually define the boundary between two different objects or parts of the same objects. In this paper we discuss the theory of the Harris corner detection and point out its disadvantage. Then it proposes an adaptive algorithm for Harris corner detection based on the neighboring point eliminating method. It reduces the amount of the calculation, and makes the corners distributing well-proportion so that avoids too many corners stay together. Experimental results show that the algorithm can detect corners more uniform distribution, and can be used in some fact applications such as image registration well.

关键词： Adaptive algorithm Image edge detection detection algorithms Object detection Change detection algorithms Image registration Eigenvalues and eigenfunctions Feature extraction Brightness Layout

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Image distance based ship detection using SAR images

Image distance based ship detection using SAR images

引用

IEEE International Conference on Networking, Sensing and Control

作者： Hua Bo Fulong Ma Information Engineering Department of Shanghai Maritime University Shanghai China Philips Research Shanghai China

A novel method is developed for ship detection in synthetic aperture radar (SRA) images, which is based on image distance computation techniques. Using a second-order hidden Markov mesh model to learn statistical models of images, one can obtain the distance of two images for the purpose of detecting ships. First, the features of an image can be extracted using a method that best matches its statistical model, which is related to dynamic programming. Second, given the state transition matrix and observation distributions within states, statistical distance between images based on the similarity of their statistical models can be estimated. Experimental results demonstrate that this ship detection algorithm can effectively enhance ship target as well as suppress speckle and has better detection precision and lower calculation complexity.

关键词： Marine vehicles Hidden Markov models Radar detection detection algorithms Synthetic aperture radar Object detection Change detection algorithms Speckle Random variables Condition monitoring

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Pavement Cracks detection Based on FDWT

Pavement Cracks Detection Based on FDWT

引用

International Conference on Computational Intelligence and Software Engineering (CiSE)

作者： Changxia Ma Wenming Wang Chunxia Zhao Feng Di Zhengli Zhu Department of Computer Science Huaihai Institute of Technology Lianyungang China School of Computer Science and Technology Nanjing University of Science and Technology of PLA Nanjing China Bereau of Water Resources Lianyungang China

Automatic detection of road cracks has been a hot topic since it reduces economic loses. It is not easy to get efficient detection algorithms because of complexity, diversity of pavement images and pavement distress's weak information. In this paper, a new approach of pavement cracks detection based on FDWT (fractional differential and wavelet transform) is proposed. Fractional differential can effectively enhance high-frequency, medium-frequency signals and non-linearly preserve low-frequency signals. After fractional differential covering module is constructed and applied to road images, pavement crack reinforcement is implemented even if the crack is weak signal in smooth area. Then in order to filter noise, wavelet transform is carried out. This approach can reinforce availably pavement images and get better effect especial for weak crack information in smooth area. Experimental results proved that the proposed detection was a valid method for the different road crack image even if there is any noise exists.

关键词： Roads Wavelet transforms Computer science Surface cracks detection algorithms Image processing 1f noise Water resources Image analysis Machine vision

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Scene cut detection in video by using combination of spatial-temporal video characteristics

Scene cut detection in video by using combination of spatial...

引用

International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Service (TELSIKS)

作者： Jugoslav Joković Danilo Đorđević Faculty of Electronic Engineering Nis Serbia

For the mainstream hard cut scene detection algorithm based on the color-histogram difference new criteria are added to increase precision and improve computational efficiency. This approach utilizes additional detection criterion based on spatial distribution of luminance blocks difference during scene cut. Also, in order to improve computational efficiency, time sampling at larger time resolutions and detection at smaller time resolutions is used. On the different video examples the results in precision and reliability are given.

关键词： Layout Change detection algorithms Signal processing algorithms Video sequences Sampling methods Histograms Computerized monitoring Motion detection Fingerprint recognition detection algorithms

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An Automatic and Dynamic Parameter Tuning of a Statistics-Based Anomaly detection Algorithm

An Automatic and Dynamic Parameter Tuning of a Statistics-Ba...

引用

IEEE International Conference on Communications (ICC)

作者： Y. Himura K. Fukuda K. Cho H. Esaki University of Tokyo Japan JST PRESTO Japan Internet Initiative Japan

The detection of anomalies in network traffic is a crucial issue affecting the security of Internet users. A statistical network anomaly detection algorithm is a promising way of detecting such anomalies, however, it has to be given appropriate parameters for accurate detection and identification. In general, it is very difficult to obtain appropriate parameter settings a priori, because network traffic is not stable in time or space. Thus, although many anomaly detection methods have been proposed, there has been little discussion about their parameter tunings. In this paper, we investigate an automatic and dynamic parameter tuning of a statistical network traffic anomaly detection method. In particular, we clarify whether one can consistently use the best parameter fixed for a certain instance; this choice clearly depends on the macroscopic and dynamic behavior of Internet traffic anomalies. We ascertain the appropriate learning period for setting a parameter of an anomaly detection algorithm based on a sketch and multi-scale gamma-function model by using real network traces measured in a trans-Pacific link over a period of six months. The main results of our study are as follows: (1) Without learning, the best parameter varies day by day. (2) With a longer learning period, the best parameter setting is affected by significant data during the learning period. (3) The appropriate period of the learning is about 3 days. (4) The performance degradation from introducing dynamic parameter tuning is 17% in the best case.

关键词： detection algorithms Telecommunication traffic Traffic control IP networks Internet Statistics Communications Society Informatics National security Degradation

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