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检索条件"主题词=Detection Algorithms"

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MLE-based order statistic automatic CFCAR detection in Weibull background

MLE-based order statistic automatic CFCAR detection in Weibu...

引用

International Conference on Advances in Computational Tools for Engineering Applications, ACTEA

作者： Souad Chabbi Toufik Laroussi Mourad Barkat Laboratoire Signaux et Systèmes de Communication Département d'Electronique SISCOM Université de Constantine Constantine Algeria Laboratoire Signaux et Systèmes de Communication SISCOM Département d'Electronique Université de Constantine Constantine Algeria Department of Electrical Engineering American University of Sharjah Sharjah UAE

In this paper, we address the problem of automatic target detection in Weibull clutter and multiple target situations, without any prior knowledge of neither the non stationary clutter statistics in which the radar operates nor the number of outliers that may be present in the reference window. In doing this, we develop the forward and backward order statistic automatic constant false censoring and alarm rates detectors based upon the maximum likelihood estimator, MLE-based F/B-OSACDC-FCAR. The censuring and detection algorithms are a two in one built detector. They select repeatedly a suitable set of ranked cells among all reference cells surrounding the cell under test to estimate the unknown background level and set the adaptive threshold accordingly. The performance of these detectors is evaluated by means of Monte Carlo simulations.

关键词： Statistics Detectors Radar detection Object detection detection algorithms Radar clutter Maximum likelihood detection Maximum likelihood estimation Testing Probability

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A fast mouth detection algorithm based on face organs

A fast mouth detection algorithm based on face organs

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Workshop on Power Electronics and Intelligent Transportation System, PEITS

作者： Qi Wang Sheng Yang Xian-wei Li Coll. of Comput. & Commun. Hunan Univ. Changsha China

Automatic mouth detection in a complex background is one of the most challenging and significant tasks in the field of computer vision and pattern recognition. A new mouth detection method that uses the relationships of face organs based on the award-winning mosaic method. The new method redesigns the policy of face blocks. Experimental results show that the algorithm can finds out the mouth region rapidly. It is also useful in a wide range. Moreover, it is effectual for complex background such as public mouth detection.

关键词： Mouth detection algorithms Face detection Computer vision Pattern recognition Face recognition Image recognition Intelligent transportation systems Eyes Humans

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MLOD: Multi-granularity local outlier detection

MLOD: Multi-granularity local outlier detection

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IEEE International Conference on Granular Computing (GRC)

作者： Liang Gao Shao-Yue Yu Yu-Pan Luo Lin Shang National Laboratory of Novel Software Technology Nanjing University Nanjing China

Outlier detection is an important data mining task, LOF(local outlier factor) was proposed to indicate the degree of outlierness, which is practical for finding local outliers. However, it is difficult to decide the neighborhood size. In this paper a multi-granularity local outlier detection(MLOD) method is proposed to organize the outlierness under multi-granularity. It finds local outliers in varying neighborhood granularity. This method applies approximation as well as grid-based partition to reduce time complexity. The theoretical results show that the time cost is linear to the size of data sets. Furthermore, the provided output and analysis can also assist users to choose the appropriate parameters. The performance of the algorithm is presented by experimenting on three generated data sets.

关键词： Indium phosphide Data mining Costs detection algorithms Laboratories Partitioning algorithms Object detection Face detection Algorithm design and analysis

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Significant cycle frequency based feature detection for cognitive radio systems

Significant cycle frequency based feature detection for cogn...

引用

International Conference on Cognitive Radio Oriented Wireless Networks and Communications

作者： Shen Da Gan Xiaoying Chen Hsiao-Hwa Qian Liang Xu Miao Department of Electronic Engineering Shanghai Jiaotong University Shanghai China Department of Engineering Science National Cheng Kung University Tainan County Taiwan

In cognitive radio systems, one of the main requirements is to detect the presence of the primary users' transmission, especially in weak signal cases. Cyclostationary detection is always used to solve weak signal detection, however, the computational complexity prevents it from wide usage. In this paper, a significant cycle frequency based feature detection algorithm has been proposed, in which only cycle frequency with significant cyclic cumulant is considered for a certain modulation mode. The proposed algorithm greatly reduces the computation complexity for cyclic feature detection. Simulation results show that the proposed algorithm has a remarkable performance gain than energy detection when supporting fast detection with low computational complexity.

关键词： Frequency Computer vision Cognitive radio Computational complexity Chromium detection algorithms Interference Matched filters Autocorrelation Gallium nitride

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An advanced spike detection and sorting system

An advanced spike detection and sorting system

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International Joint Conference on Neural Networks (IJCNN)

作者： Yuan Yuan Chenhui Yang Jennie Si Department of Electrical Engineering Arizona State University Tempe AZ USA

This paper proposes a comprehensive new neural spike detection and sorting system. As a critical first step to all neuroscientific studies of the nervous system using chronically implanted electrodes in the brain areas of interest, high performance neural spike detection and sorting from the massive amount of continuously recorded neural data is a challenging task, especially in real time applications such as brain machine interface. Many existing spike detection and sorting systems use simple thresholding as the first step to admit a large number of possible spikes for further sorting using various clustering algorithms. Significant efforts have gone into developing sophisticated sorting algorithms, many of which are time consuming in applications. In this paper, we develop a new system that is based on a reliable detection algorithm using multiple correlations of wavelet coefficients, which is robust and can be implemented in real time. Because of the advanced detection step, the system becomes less demanding on the performance of the sorting or clustering algorithms. This has simplified the overall system, and made real time interface and other real time applications possible. We tested the newly proposed system extensively, compared with several popular systems including commercial packages. While most thresholding based detection systems usually create a large number of false alarms, test results show that our proposed system on both artificial and real neural data have produced few false alarms but with high detection rates.

关键词： Sorting Real time systems Clustering algorithms Brain System testing Nervous system Electrodes detection algorithms Wavelet coefficients Robustness

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Fast Pedestrian detection in Dense Environment with a Laser Scanner and a Camera

Fast Pedestrian Detection in Dense Environment with a Laser ...

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IEEE Conference on Vehicular Technology (VTC)

作者： G. Gate A. Breheret F. Nashashibi Robotics Laboratory Mines Paris-Tech Paris France Robotics Laboratory Mines ParisTech and INRIA-IMARA team Le Chesnay France

Because pedestrians have neither well defined shapes nor well defined behaviors, detecting and tracking them from a moving vehicle remains a difficult task. To serve as an onboard driver assistance system, a perception algorithm also needs to be both fast and robust. We present in this paper a system that reaches a good level of reliability by efficiently combining the data of two sensors - a laser scanner and a camera - while remaining tractable on CPU limited mobile architectures.

关键词： Cameras Laser fusion Robustness Shape Robots detection algorithms Recursive estimation Bayesian methods Filters Laboratories

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Exploiting semantics for event detection systems

Exploiting semantics for event detection systems

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IEEE International Conference on Pervasive Computing and Communications (PerCom)

作者： Ronen Vaisenberg School of Information and Computer Sciences University of California Irvine USA

This dissertation is building towards a flexible and scalable middleware for sentient spaces wherein sensors are used to observe the state of a physical environment in real time to create awareness which, in turn, is used to build applications that bring new functionalities and/or new efficiencies to the environment. Examples of such sentient spaces could be as varied as smart buildings that use video sensors for surveillance or for building pervasive applications such as person locator to dynamically instrumented crisis sites wherein sensors carried by first responders and/or brought to crisis sites are used to monitor the crisis site and the progress of response activities. The key goal of this work is towards developing a robust and scalable middleware technology that can handle challenges related to heterogeneity of sensors, limited resources (e.g., network bandwidth), and the need for rapid deployment (e.g., self-calibration of sensing), and programmability (e.g., hiding complexity of sensor and sensor programming from the application writers).

关键词： Event detection Sensor systems Monitoring Intelligent sensors Clustering algorithms Middleware Sensor phenomena and characterization detection algorithms Physics computing Sensor systems and applications

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Diffusion LMS-based distributed detection over adaptive networks

Diffusion LMS-based distributed detection over adaptive netw...

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Asilomar Conference on Signals, Systems & Computers

作者： Federico Cattivelli Ali H. Sayed Department of Electrical Engineering University of California Los Angeles CA USA

ISBN: (纸本)9781424458257

We consider the problem of distributed detection, where a set of nodes are required to decide between two hypotheses based on their measurements. In diffusion implementations, nodes communicate with their neighbors and no fusion center is needed. In previous work we proposed a distributed detection scheme which was based on diffusion least-squares techniques. In this work we consider the case where nodes utilize diffusion LMS techniques instead. The proposed detector is capable of tracking changes in the active hypothesis. We analyze the performance of the detector, and provide simulation results comparing with other cooperation schemes.

关键词： Adaptive systems Time measurement Least squares approximation Detectors Iterative algorithms Resonance light scattering Performance analysis Analytical models detection algorithms Electric variables measurement

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RESTORATION OF DIGITIZED VIDEO SEQUENCES: AN EFFICIENT DROP-OUT detection AND REMOVAL FRAMEWORK

RESTORATION OF DIGITIZED VIDEO SEQUENCES: AN EFFICIENT DROP-...

引用

International Conference on Image Processing

作者： Hagen Kaprykowsky Mohan Liu Patrick Ndjiki-Nya Image Communication Group Image Processing Department Fraunhofer Institute for Telecommunications - Heinrich-Hertz-Institut

ISBN: (纸本)9781424456536;9781424456543

Millions of hours of valuable audiovisual content is endangered or already destroyed. Today, restoration is mainly done manually, which is time-consuming, costly and thus simply infeasible for large amounts of data. For this reason, automation of restoration efforts is of major importance to win the race against time. In this paper, a framework for efficient drop-out detection and restoration is presented. This artifact class is one of the most frequently occurring in video archives. The proposed detection algorithm is a two-pass approach, where frames of the potentially deteriorated video sequences are classified into valid and suspect based on global color statistics of the images. Suspect pictures are further submitted to local, quad-tree-based analysis for refined evaluations. This yields a subset of identified damaged pictures with accurately localized defects. Detected defective frames are restored using a motion compensation-based approach. Experiments on a data set based on video sequences of the "PrestoSpace" project show very promising results.

关键词： Restoration Drop-out Defect detection Defect removal Motion compensation Quad-tree restoration quaternary tree Motion compensation Defect detection Videotapes detection algorithms Dropping out Video sequences

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Anomaly detection using projective Markov models in a distributed sensor network

Anomaly detection using projective Markov models in a distri...

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IEEE Conference on Decision and Control

作者： Sean Meyn Amit Surana Yiqing Lin Satish Narayanan Electrical and Computer Engineering and the Coordinated Sciences Laboratory University of Illinois Urbana-Champaign USA United Technologies Research Center Inc. East Hartford CT USA

ISBN: (纸本)9781424438716

The paper develops application of techniques from robust and universal hypothesis testing for anomaly detection and change-point detection in dynamic, interconnected systems. This theory is extended using the concept of projected Markov models originally proposed by Claude Shannon. Also presented is a detailed application to anomaly detection from people movements patterns in buildings.

关键词： Buildings Robustness Monitoring detection algorithms Detectors Tracking Predictive models Traffic control Data security Information security

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