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检索条件"主题词=Detection algorithms"

共 7327 条记录，以下是291-300 订阅

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Comparative Study on Foreground detection algorithms for Human detection

Comparative Study on Foreground Detection Algorithms for Hum...

引用

International Conference on Image and Graphics (ICIG)

作者： Y. Benezeth B. Emile C. Rosenberger Laboratoire Vision et Robotique-UPRES EA 2078 ENSI de Bourges-Université d''Orléans Bourges France

The objective of this paper is to develop an approach to objectively evaluate foreground detection algorithms. The purpose of the desired application is human detection in images sequences. This paper presents in a first part the state of the art on foreground detection algorithms. In a second part, we use realistic synthetic videos to perform our evaluation. This kind of videos is very interesting for the evaluation study because it permits to evaluate the influences of some artifacts (changing light, video quality, shadow). We use a common metric to quantify the efficiency of the 11 selected algorithms. Time computation is also considered.

关键词： detection algorithms Humans Videos Pixel Image sequences Intelligent robots Protocols Image databases Graphics Robot vision systems

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Evaluation and performance comparison of power swing detection algorithms

Evaluation and performance comparison of power swing detecti...

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IEEE General Meeting Power& Energy Society

作者： H. Khoradshadi-Zadeh Dept. of Electr. Eng. Birjand Univ. Iran

This paper presents performance comparisons and evaluations of several power swing detection algorithms. Any sudden change in the configuration or the loading of an electrical network causes power swing between the load concentrations of the network. In order to prevent the distance protection from tripping during such conditions, a power swing blocking is utilized. The decreasing impedance, the Vcos/spl phi/ and the superimposed currents methods are conventional algorithms for power swing detection. In this paper, the behavior of these algorithms is evaluated. Different conditions have been generated by EMTDC software and voltage and current waveforms have been given to the power swing detectors. Operation of the power swing detectors has been investigated for different conditions and the operation of different algorithms are compared.

关键词： detection algorithms Protective relaying Power system relaying Impedance Power system simulation Voltage Power system protection Power system faults Power system modeling Circuit faults

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A comparative study of various community detection algorithms in the mobile social network

A comparative study of various community detection algorithm...

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Nirma University International Conference on Engineering (NUiCONE)

作者： Ankit Didwania Zunnun Narmawala IT Department Faculty of Technology Dharmsinh Desai University Nadiad Gujarat India Institute of Technology Nirma University Ahmedabad Gujarat India

Mobile social network is a type of delay tolerant network of mobile devices in which there is no end-to-end path available in advance for communication. It works on the principle of a store-carry-forward mechanism. The community is a very useful property of the mobile social network as humans are social animals and they like to live in a community. Such community structure enables efficient communication between devices carried by humans without any infrastructure. We have analyzed various community detection methods and identified those suitable for mobile social network. We have also analyzed various existing distributed community detection algorithms in mobile social networks based on important parameters like complexity and type of community detected. Such analysis will help in discovering strengths and shortcomings of various existing algorithms. As the mobile social network is self-organizing real network working on highly resource constraint mobile devices, it is necessary to enable each mobile device to detect its own community with minimal information, computation and space requirements. This is a very challenging task and very little work is done in it. So there is an immense opportunity available for research in this area.

关键词： Social network services Mobile computing Mobile communication Mobile handsets detection algorithms Clustering algorithms Delays

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Evaluating Driving Fatigue detection algorithms Using Eye Tracking Glasses

Evaluating Driving Fatigue Detection Algorithms Using Eye Tr...

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International IEEE/EMBS Conference on Neural Engineering

作者： Xiang-Yu Gao Yu-Fei Zhang Wei-Long Zheng Bao-Liang Lu Dept. of Comput. Sci. & Eng. Shanghai Jiao Tong Univ. Shanghai China

ISBN: (纸本)9781467363877

Fatigue is a status of human brain activities, and driving fatigue detection is a topic of great interest all over the world. In this paper, we propose a measure of fatigue produced by eye tracking glasses, and use it as the ground truth to evaluate driving fatigue detection algorithms. Particularly, PERCLOS, which is the percentage of eye closure over the pupil over time, was calculated from eyelid movement data provided by eye tracking glasses. Experiments of a vigilance task were carried out in which both EOG signals and eyelid movement were recorded. The evaluation results of an effective EOG-based fatigue detection algorithm convinced us that our proposed measure is an appropriate candidate for evaluating driving fatigue detection algorithms.

关键词： Fatigue Glass Feature extraction Tracking detection algorithms Electrooculography Eyelids

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Review Over Anomaly detection algorithms for Detecting SYN Flooding Attacks

Review Over Anomaly Detection Algorithms for Detecting SYN F...

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Student Conference on Engineering Sciences and Technology, SCONEST

作者： Riaz A. Shaikh Ahmad Ali Iqbal Kashan Samad Institute of Information Technology NUST Institute of Information and Technology Rawalpindi Pakistan

Network anomalies usually refer to the conditions when network operations diverge from the normal behavior. Anomaly detection in an IP network is a very complex task, because it is dependent upon the nature of the data that is available for the analysis. In this paper we have given the overview of two statistical based anomaly detection algorithms that are adaptive threshold algorithm and cumulative SUM algorithm especially with respect to the anomaly that is occurred due to SYN flooding attacks. In the case of high intensity SYN flooding attacks both were good and have less false alarm ratio where as in the case of low intensity attacks adaptive threshold algorithm performance degrade and shows high false alarm where as in the case of cumulative sum algorithm its performance remain same with lesser false alarm ratio.

关键词： detection algorithms Floods Computer crime File servers Broadcasting Telecommunication traffic IP networks Protocols Storms Network servers

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Performance comparison of Wavelet based OFDM (WOFDM) V-BLAST MIMO system with different detection algorithms

Performance comparison of Wavelet based OFDM (WOFDM) V-BLAST...

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International Conference on Emerging Technologies, ICET

作者： Muhammad Yasir M. J. Mughal N.D. Gohar S. A. Moiz GIK Institute of Engineering Science and Technology Topi Khyber Pakhtunkhwa Pakistan Department of Electronic Engineering Mohammad Ali Jinnah University Islamabad Pakistan

In this article, design, performance and simulation of wavelet based OFDM V-BLAST MIMO system has been discussed. Wavelet based OFDM technique is based upon orthonormal wavelets bases generated from Haar quadrature mirror filter (QMF) bank. The BER performance of this system has been observed with three different V-BLAST detection algorithms. The three V-BLAST detection algorithms implemented in this article are: zero forcing (ZF), minimum mean squared error (MMSE) and QR-decomposition based V-BLAST detection algorithms.

关键词： MIMO detection algorithms Wireless communication Receiving antennas Transmitting antennas Bandwidth Fading OFDM modulation Design engineering Mirrors

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Towards designing secure in-vehicle network architectures using community detection algorithms

Towards designing secure in-vehicle network architectures us...

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IEEE Vehicular Networking Conference (VNC)

作者： Pierre Kleberger Nasser Nowdehi Tomas Olovsson Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Volvo Car Corporation Gothenburg Sweden

Efforts in securing the in-vehicle network have resulted in a number of proposed security mechanisms in recent years. However, so far little attention has been given to the actual architecture of the in-vehicle network. An approach within in-vehicle network design is to divide the network into domains, where each domain consists of a set of Electronic Control Units (ECUs) that handles some united functionality, e.g., body control, powertrain, and telematics. Still, this approach is based on “best engineering practice” and there is room for improvements. In this paper, we study real traffic from a modern car and we try to divide the in-vehicle network into domains using automated partitioning algorithms. To find the optimum division, we select four community detection algorithms, known from social network analysis, and we evaluate their ability to find these domains. We conclude that community detection algorithms can be used to identify in-vehicle domains based on the message types (signals) used in the in-vehicle network and we demonstrate this by applying the algorithms to real data. The approach is not limited to only message types, but domains can also be identified based on other criteria, such as frequency of messages, payload sizes, or Automotive Safety Integrity Levels (ASILs). We also conclude that the identification of good domains can facilitate the implementation of security measures. Therefore, we believe that the approach has great potential to help engineers in deriving secure in-vehicle network architectures during the design of a vehicle.

关键词： Communities Vehicles Security Partitioning algorithms detection algorithms Image edge detection Algorithm design and analysis

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Development of Lane and Zebra Crossing Marker detection algorithms

Development of Lane and Zebra Crossing Marker Detection Algo...

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Device Intelligence, Computing and Communication Technologies, (DICCT), International Conference on

作者： Vivek Chamoli R Gowri V P Dubey Jyoti Kandpal Jyoti Joshi Divesh Kumar Dept. of Electronics & Communication Engineering Graphic Era Hill University Dehradun India Dept. of Comupter Science & Engineering Graphic Era Hill University Dehradun India

This research involves using an object recognition system and an ancillary image sensor to detect lane markers and zebra crossings on a roadway in a vehicle. To perform this detection, these steps have been followed: take a picture of the scene, digitize it, normalize it, define a search area within it, look for lane and zebra markers within it. The Lane Tracking for Driving System was created to assist drivers in making lane departure decisions, to lessen concentration breaks, and to avoid accidents while driving. To offer a way to detect a specific traffic violation—namely, stopping on a zebra crossing at a traffic signal rather than following behind it—and to offer a workaround. In the proposed work, systems are implemented and improved using adaptive algorithms. MATLAB’s image processing toolbox is used to design and implement the proposed algorithm.

关键词： Image sensors Image processing Adaptive algorithms Communications technology Object recognition detection algorithms Vehicles

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Evaluation of multi-component Electrocardiogram beat detection algorithms: Implications of three different noise artifacts

Evaluation of multi-component Electrocardiogram beat detecti...

引用

Computers in Cardiology (CinC)

作者： T. Last C.D. Nugent F.J. Owens D.D. Finlay Faculty of Engineering University of Ulster UK

Motion artifacts, caused by changes in the electrode-skin impedance, electromyographic (EMG) interference, caused by muscle contractions, and possible baseline drifts are three of the most common sources of noise present in ECG recordings. The present study investigates the effects of these noise sources on the performance of ECG beat detection algorithms. Four different beat detection methods were used to evaluate the influence of noise sources with varying signal to noise ratios (SNRs). A database consisting of recordings from approximately 100 subjects consisting of approximately 3000 cardiac cycles was used for evaluation. Hence, 1200 records were subsequently tested by the detectors after adding three different noise sources with four different SNRs of 24 dB, 12 dB, 6 dB and -6 dB to the original 100 records. The four classifiers achieved beat detection results from 98% down to 68% for correctly detected QRS-complexes at SNRs between 24 dB and 6 dB.

关键词： detection algorithms Electrocardiography Signal to noise ratio Impedance Electromyography Interference Muscles Databases Testing Detectors

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Novel Peak detection algorithms for Pileup Minimization in Gamma Ray Spectroscopy

Novel Peak Detection Algorithms for Pileup Minimization in G...

引用

IEEE Instrumentation and Measurement Technology Conference

作者： M. W. Raad L. Cheded Computer Engineering Department King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Systems Engineering Department King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia

A fast waveform sampling facility has been recently developed and integrated into the VAX-based data acquisition system at the Center for Applied Physical Sciences (CAPS). This study uses the above facility in developing algorithms for digitally determining the basic pulse parameters and tackling the problem of pulse pile-up in Gamma-ray spectroscopy. A number of parameter estimation and digital online peak localisation algorithms are being developed, including a pulse classification technique which uses a simple peak search routine based on the smoothed first derivative method, which gave a percentage error of peak amplitude of less than 1%. The classification technique has the unique feature of cutting down the computation largely by only allowing the event of interest to be executed by a particular algorithm. The set-up was also tested with random signals from a 137 Cs test source. Gamma pulses from a 3" Na(TI) scintillation detector were captured as single and double pulses for the purpose of testing the peak detection algorithms. The pulse classification technique was tested successfully on a TMS320C6000 high performance floating-point processor yielding a reduction of the execution time to 2 msec

关键词： detection algorithms Minimization methods Spectroscopy Tail Testing Data engineering Systems engineering and theory Event detection Digital signal processing Instrumentation and measurement

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