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检索条件"主题词=detection algorithms"

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Engineering Solution to Nuclear Material detection at Ports: Introducing the Novel iMASS Paradigm

Engineering Solution to Nuclear Material Detection at Ports:...

引用

International Conference on Tools for Artificial Intelligence (ICTAI)

作者： M. Alamaniotis J. Young J. Perry S. Xiao V. Agarwal P. Forsberg R. Gao C. Choi L.H. Tsoukalas T. Jevremovic School of Nuclear Engineering Purdue University West Lafayette IN USA Nuclear Engineering Program University of Utah Salt Lake UT USA

detection of special nuclear material (SNM) hidden in cargo containers is considered to be one of the major challenges for homeland security. SNM impose a significant threat for public safety since they can be converted into nuclear weaponry and used for potential terrorist attacks. In this paper we present who we can fill the existing gap in quickly but accurately detecting hidden SNM. Synergism of Monte Carlo methods and intelligent control paradigm provides a novel frame for automated cargo interrogation and final decision making. Human operator is assumed to not be the part of the procedure while the powerful detection algorithms are used with fuzzy logic tools to indicate whether the container should be singled out for manual search or not. In this paper the general frame of our so called iMASS (intelligent Model Assisted Sensing System) is presented.

关键词： Containers Terrorism Safety Weapons Intelligent control Decision making Humans detection algorithms Fuzzy logic Power system modeling

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Outlier detection via localized p-value estimation

Outlier detection via localized p-value estimation

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Annual Allerton Conference on Communication, Control, and Computing

作者： Manqi Zhao Venkatesh Saligrama Department of Electrical and Computer Engineering Boston University Boston MA USA

ISBN: (纸本)9781424458707

We propose a novel non-parametric adaptive outlier detection algorithm, called LPE, for high dimensional data based on score functions derived from nearest neighbor graphs on n-point nominal data. Outliers are predicted whenever the score of a test sample falls below ¿, which is supposed to be the desired false alarm level. The resulting outlier detector is shown to be asymptotically optimal in that it is uniformly most powerful for the specified false alarm level, ¿, for the case when the density associated with the outliers is a mixture of the nominal and a known density. Our algorithm is computationally efficient, being linear in dimension and quadratic in data size. The whole empirical receiving operating characteristics (ROC) curve can be derived with almost no additional cost based on the estimated score function. It does not require choosing complicated tuning parameters or function approximation classes and it can adapt to local structure such as local change in dimensionality by incorporating the technique of manifold learning. We demonstrate the algorithm on both artificial and real data sets in high dimensional feature spaces.

关键词： Testing Detectors Nearest neighbor searches Training data Level set detection algorithms Cost function Function approximation Change detection algorithms Support vector machines

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A New Corner detection Algorithm with SUSAN Fast Hierarchical Method

A New Corner Detection Algorithm with SUSAN Fast Hierarchica...

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International Asia Symposium on Intelligent Interaction and Affective Computing (ASIA)

作者： Jie Zhao Haichao Ma Guozun Men College of Electronic and Information Engineering Hebei University Baoding Hebei China College of Economics Hebei University Baoding Hebei China

A new fast corner detection algorithm is proposed by the discriminant introduction of the corner "quality¿ considering the defect of the traditional algorithm using SUSAN method. With the fast hierarchical algorithm based on SUSAN method, the coarse positions of corners are quickly determined firstly. Secondly, the discriminant introduction of the corner "quality" reduces the amount of corners. Then, the precise search finds the exact positions of corners. The experimental results show that this method greatly improves the speed of operation and saves lots of time. Besides, the effect of the corners matching is also better.

关键词： detection algorithms Wavelet transforms Gray-scale Fourier transforms Image edge detection Computational complexity Educational institutions Asia Economic forecasting Pixel

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Falls event detection using triaxial accelerometry and barometric pressure measurement

Falls event detection using triaxial accelerometry and barom...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Federico Bianchi Stephen J. Redmond Michael R. Narayanan Sergio Cerutti Branko G. Celler Nigel H. Lovell Department of Biomedical Engineering Politecnico di Milano Milano Italy Graduate School of Biomedical Engineering University of New South Wales Sydney NSW Australia Biomedical Systems Laboratory University of New South Wales Australia

A falls detection system, employing a Bluetooth-based wearable device, containing a triaxial accelerometer and a barometric pressure sensor, is described. The aim of this study is to evaluate the use of barometric pressure measurement, as a surrogate measure of altitude, to augment previously reported accelerometry-based falls detection algorithms. The accelerometry and barometric pressure signals obtained from the waist-mounted device are analyzed by a signal processing and classification algorithm to discriminate falls from activities of daily living. This falls detection algorithm has been compared to two existing algorithms which utilize accelerometry signals alone. A set of laboratory-based simulated falls, along with other tasks associated with activities of daily living (16 tests) were performed by 15 healthy volunteers (9 male and 6 female; age: 23.7 plusmn 2.9 years; height: 1.74 plusmn 0.11 m). The algorithm incorporating pressure information detected falls with the highest sensitivity (97.8%) and the highest specificity (96.7%).

关键词： Event detection Pressure measurement Signal processing algorithms detection algorithms Accelerometers Sensor phenomena and characterization Sensor systems Wearable sensors Signal processing Signal analysis

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Covariant Support Region and detection Algorithm Based on LoG Corners

Covariant Support Region and Detection Algorithm Based on Lo...

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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： Yawei Liu Jianwei Li School of Science Chongqing Jiaotong University Key Lab on Opto-Electronic Technique of State Educat School of Opto-electronic Engineering Chongqing University Key Lab on Opto-Electronic Technique of S

ISBN: (纸本)9781424447749

detection of Local feature covariant region is a new technology of image contents and image semantic representations, and it has become an important foundation of the image recognition, learning and understanding. First, a Laplace of Gaussian corner detection method is proposed based on edge contour curves, in the meantime, a new local feature descriptor, named covariant support region, is introduced. Then, a detection algorithm of covariant support region is framed, which is covariant for rotation and scale transformation. Comparing with previous studies, the computational complexity of proposed algorithm is significantly reduced by this method. The experiments data indicate that the method proposed in this papaer has good performance on higher accuracy, higher repeatability, and lower complexity.

关键词： detection algorithms local image feature corners Experimental data complexity classes new technology corner detection method Region

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An efficient approach to still image copy detection based on SVD and block partition for digital forensics

An efficient approach to still image copy detection based on...

引用

IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS)

作者： XiaoBing Kang ShengMin Wei The Key Laboratory of Contemporary Design and Integrated Manufacturing Technology Ministry of Education Northwestern Polytechnical University Xi'an Shaanxi China

As an important component of passive media forensics (PMF), content-based copy detection (CBCD) is appropriate for identifying piracy of digital content and preventing falsified evidence. In this paper, we propose a novel and efficient CBCD scheme for identifying different altered versions of original images. We employ singular value decomposition (SVD) and block partition to improve the robustness and discriminability of image content identification. To examine the validity of proposed copy detection algorithm, 32 attacks including geometric transformation, signal processing and image manipulation, are applied to copyrighted images to generate large virtual altered images. Experimental results demonstrate the efficacy of the proposed copy detection scheme in withstanding various attacks.

关键词： Digital forensics Watermarking Internet Educational technology Singular value decomposition detection algorithms Protection Image processing Signal processing Laboratories

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Redundant rules detection in EEG fuzzy classifier

Redundant rules detection in EEG fuzzy classifier

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IEEE International Conference on Intelligent Engineering Systems (INES)

作者： David Coufal Academy of Sciences Prague Czech Republic

In the paper we present the application of the redundancy detection algorithm for the purpose of simplification of rule base of a radial implicative fuzzy classifier. The classifier is built up to detect different lev... 详细信息

关键词： Electroencephalography Fuzzy systems Spectrogram Fuzzy sets Computer science Chromium Electronic mail Application software detection algorithms Monitoring

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Towards robust skin colour detection and tracking

Towards robust skin colour detection and tracking

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IEEE Instrumentation and Measurement Technology Conference

作者： Nuwan Gamage Rini Akmeliawati Kuang Ye Chow School of Engineering Monash University Sunway Malaysia Department of Mechatronics Engineering International Islamic University Malaysia Kuala Lumpur Malaysia

Skin colour modelling has been a popular research topic over the years due its possible practical applications. Varying skin tones makes modelling of skin colour as one of the most complex and challenging task. Accuracy and performance of skin detection and tracking highly depends on the skin model in use and the tracking method. In order to perform in real time, skin detection and tracking algorithm has to be computationally efficient and robust. This paper presents our effort on designing such an algorithm with a number of simple cascaded filters. It has been successfully implemented and tested with number of popular independent image databases available on the internet. This algorithm guarantees an accuracy rate of 70%.

关键词： Robustness Skin Image databases Testing Lighting detection algorithms Head Statistical analysis Artificial intelligence Filters

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An Artificial Vision-Based Lane detection Algorithm

An Artificial Vision-Based Lane Detection Algorithm

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International Symposium on Computer Science and its Applications, CSA

作者： Nadra Ben Romdhane Mohamed Hammami Hanene Ben-Abdallah Department of Computer Science Multimedia Information Systems and Advanced Computing Laboratory Sfax Tunisia

ISBN: (纸本)9781424449453;9781424449460

In this paper, we present a lane detection algorithm based on hough transform and linear parabolic fitting. The candidate pixels are collected after image contrast enhancement while using morphological filters. The algorithm was tested on image sequences we filmed on the roads of Tunisia and on images from the PETS2001 dataset provided by Essex University (England). These images present different environment conditions such as shadow, partial coverage of the markings by obstacles, different lane markings that can be blurred or well contrasted, and different weather conditions.

关键词： detection algorithms Road safety Road accidents Filters Surface morphology Road transportation Computer science Multimedia systems Multimedia computing Information systems

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Vibration based damage detection in smart nonuniform thickness laminated composite beams

Vibration based damage detection in smart nonuniform thickne...

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IEEE Toronto International Conference on Science and Technology for Humanity (TIC-STH)

作者： Hamidreza Ghaffari Abolghassem Zabihollah Esmaeel Saeedi Roya Ahmadi School of Science and Engineering Sharif University of Technology Kish Iran Semnan University Semnan Iran Iran Tavanir Organization Tehran Iran

ISBN: (纸本)9781424438778;9781424438785

Laminated composite beams with non-uniform thickness are being used as primary structural elements in a wide range of advanced engineering applications. Tapered composite structures, formed by terminating some of the plies, create geometry and material discontinuities that act as sources for delamination initiation and propagation. Any small damage or delamination in these structures can progress rapidly without any visible external signs. Due to this reason early detection of damage in these systems during their service life is receiving increasing attention. The presence of a crack in a component or structure leads to changes in its global dynamic characteristics results in decreases in the natural frequencies and modifications of the mode shapes of the component or structure. The present work aims to investigate the influences of delamination on the natural frequencies, frequency and voltage responses of smart non-uniform thickness laminated composite beams. In order to guarantee the continuity of curvature at element interfaces, particularly at ply drop-off locations, a higher-order finite element model by considering the electro-mechanical coupling effect is used which can accurately and efficiently represents the dynamic responses of the structure for forced/random stimuli and provide accurate results using fewer elements.

关键词： Delamination Laminates Helicopters Stress Resins Finite element methods Payloads Frequency response detection algorithms Pattern recognition

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