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检索条件"主题词=detection algorithms"

共 7428 条记录，以下是1631-1640 订阅

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Nonnegative Matrix Factorization Algorithm with Two Attribute Matrices for Community detection

Nonnegative Matrix Factorization Algorithm with Two Attribut...

引用

IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)

作者： Yingying Zhao Hui Xu Cheng Zhou School of Information Science and Technology Nantong University Nantong China

ISBN: (数字)9781728170053

ISBN: (纸本)9781728170060

Community detection based on nonnegative matrix factorization (NMF) has the advantages of clear physical meaning, simple calculation and strong interpretability, but its accuracy needs to be improved. For this reason, this paper puts forward the community detection algorithm using NMF with two attribute information matrices(2AMNMF). First of all, two attribute information matrices are created from calculating similarity between the entity and entity, then one of which is decomposed into two non-negative matrices by NMF, another attribute information matrix is added into objective function for optimization. Evaluation is made by modularity Q. The experiment results show that the algorithm of community detection we proposed is more accurate than the original NMF algorithm.

关键词： Motion pictures Linear programming Matrix decomposition Partitioning algorithms Approximation algorithms Symmetric matrices detection algorithms

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Zero-Crossing detection Algorithm Based on Narrowband Filtering

Zero-Crossing Detection Algorithm Based on Narrowband Filter...

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IEEE Student Conference on Electric Machines and Systems

作者： Zunxian Wang Shouyuan Wu Mingxu Wang Yongxin Yang Xiaoming Luan Weichao Li School of Electrical Engineering Shandong University Jinan China

ISBN: (数字)9781728156224

ISBN: (纸本)9781728156231

To deal with the simultaneous jump of phase, frequency and amplitude in the transient process of signals and improve the accuracy of zero-crossing detection, this paper proposes a fast zero-crossing detection algorithm for this complex condition. The algorithm initially normalizes the electrical quantity before it passes through the narrow-band filter. Then the algorithm is used to calculate the zero-crossing time and eliminate the zero offset and jitter. Finally, the phase information of positive and negative zero crossing points is obtained. Simulation results show that the algorithm improves the tracking accuracy based on higher response speed and has strong robustness in a complex grid environment. It is simple to implement, which can meet the requirements of capacitors and other equipment switching control.

关键词： Switches Filtering algorithms Jitter Robustness detection algorithms Power harmonic filters Narrowband

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An automatic siren detection algorithm using Fourier Decomposition Method and MFCC

An automatic siren detection algorithm using Fourier Decompo...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Binish Fatimah A. Preethi V. Hrushikesh Akhilesh Singh B. Harshanikethan R. Kotion CMR Institute of Technology Bengaluru

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

In this work, an automatic ambulance detector has been proposed using features extracted from the siren of the ambulance. The smart ambulance detector can reduce the time required by an ambulance to reach their destination in emergency situations. In the present scenario, the cars are designed to provide more and more luxury to the driver and insulation from the outside noise. Along with the traffic noise, the siren sounds also get muffed, leaving the drivers clueless to the emergency vehicles in their vicinity. In these cases, the proposed system can be used to alert the driver about the approaching emergency vehicle. The proposed system uses audio sensors to record the siren sound and pre-process the acquired signal using a bandpass filter. In this work, two sets of features are computed, the first set consists of Mel-frequency cepstrum coefficients of the filtered signal. For the second set, the signal is decomposed in frequency domain using Fourier decomposition method. Statistical features such as kurtosis, energy, and variance are computed from each of the sub-bands. Relevant features are selected based on the Kruskal-Wallis test. The selected feature set is then used to train a machine learning model to identify siren sounds from the background traffic noise. In this work, we have compared the performance of various machine learning algorithms like kNN, SVM and ensemble bagged trees to select the best model. The dataset used in this work includes signals from two publicly available datasets with ambulance siren audio files and traffic sound files, and also audio data collected from different sources on the internet. We have also recorded the siren sounds in city traffic conditions.

关键词： Machine learning algorithms Computational modeling Cepstrum Detectors Feature extraction detection algorithms Vehicles

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Pneumonia detection in chest X-rays: a deep learning approach based on ensemble RetinaNet and Mask R-CNN

Pneumonia Detection in chest X-rays: a deep learning approac...

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International Conference on Advanced Cloud and Big Data (CBD)

作者： Liu mao Tan Yumeng Chen Lina College of Physics and Electronic Information Engineering Zhejiang Normal University Jinhua China College of Physics and Electronic Information Engineering Zhejiang Normal Univercity Jinhua China

The following topics are dealt with: learning (artificial intelligence); feature extraction; convolutional neural nets; pattern classification; traffic engineering computing; cloud computing; recurrent neural nets; de... 详细信息

关键词： Deep learning Training Radiography Performance evaluation Lung Robustness detection algorithms

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detection of Cyclostationary Electromagnetic Emissions Using Degree of Cyclostationarity

Detection of Cyclostationary Electromagnetic Emissions Using...

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Baltic URSI Symposium (URSI)

作者： Mikhail Nuzhnov Andrey Baev Maxim Konovalyuk Anastasia Gorbunova Yury Kuznetsov Wane Sidina Moscow Aviation Institute Moscow Russian Federation eV-Technologies Caen France

ISBN: (数字)9788394942199

ISBN: (纸本)9781728157887

detection and localization of physical radiating sources allows to allocate hotspots with substantial emitting power on the surface of the printed circuit board (PCB) of the electronic device. Electromagnetic emissions caused by data transferring signals can be mathematically described by cyclostationary stochastic processes. The optimal detection of cyclostationary stochastic process with known two-dimensional autocorrelation function (ACF) assumes two-dimensional crosscorrelation between the shifted product of the stochastic process and relevant ACF. The proposed detection algorithm is based on the degree of cyclostationarity (DCS), defining by comparison of evaluated ACFs obtained from the measured realizations of stochastic process. Experimental verification of the proposed algorithm was implemented by near-field scanning of two spatially distributed sources with different cyclic frequencies on the surface of the PCB.

关键词： Time-frequency analysis Correlation Stochastic processes Time measurement Electromagnetics detection algorithms Surface treatment

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An Electric Fire Flame detection Algorithm Based on Temporal Convolution

An Electric Fire Flame Detection Algorithm Based on Temporal...

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International Conference on Computer Engineering and Applications (ICCEA)

作者： WEI Chao DENG Jie-qing CHEN Guang ZHU Bo Lina Li Luefu Zhu State Grid Jiangsu Electric Power CO. LTD Nanjing China State Grid Electric Power Research Institute CO. LTD Nanjing China Anhui Jushi Technology Co. Ltd

ISBN: (数字)9781728159041

ISBN: (纸本)9781728159058

Flame detection algorithm is very important in electric power fire prevention. In order to solve the problems of insufficient generalization force, high false alarm rate and poor adaptability of flame detection algorithm, a power video flame detection algorithm based on temporal convolution, which integrates TCML (Temporal-Convolution-based meta-learner) and FHOG (Fused Histogram of Oriented Gradient). The candidate region set was determined by particle filter, and FHOG feature was extracted; Abstract features are extracted with TCML; The distance between features was determined by using the kelley-klein metric learning criterion, and the flame was identified. The experimental results show that the proposed flame detection algorithm has high accuracy, good image fusion and generalization ability, and strong adaptability to the environment.

关键词： Fires Feature extraction detection algorithms Convolution Task analysis Heuristic algorithms Measurement

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A fatigue driving detection algorithm based on weighted D-S evidence theory

A fatigue driving detection algorithm based on weighted D-S ...

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Chinese Automation Congress (CAC)

作者： Xiaohui Zhang Haitao Gan Long Chen School of Automation Hangzhou Dianzi University Hangzhou China School of Electronic Information Hangzhou Dianzi University Hangzhou China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Fatigue driving detection is of great significance to public traffic safety. Traditional fatigue driving detection algorithm pursues the minimum classification error rate and ignores the loss caused by different misclassification. However, fatigue driving detection algorithm should pay more attention to the high cost misclassification samples to minimize the overall loss of the learning model. In order to solve this problem, the cost-sensitive learning and Dempster-Shafer evidence theory (D-S evidence theory) are combined to obtain a robust and good performance ensemble classifier.

关键词： Fatigue Training Evidence theory detection algorithms Error analysis Matrix converters Classification algorithms

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A Spectral Clustering-Based Community detection Algorithm for RDF Graphs

A Spectral Clustering-Based Community Detection Algorithm fo...

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Artificial Intelligence (WSAI), World Symposium on

作者： Gustaph Sanga Xingxing Hao School of Artificial Intelligence Xidian University Xi’an China

ISBN: (数字)9781728167794

ISBN: (纸本)9781728167800

Community detection is a widely explored research area in complex networks. Communities are a set of components with highly intra-community similarities and little inter-community similarities. Detecting community structure in complex directed and labeled graphs is an inter-disciplinary research area with great importance in real-world knowledge domains. This paper provides a precise description of a new complex directed and labeled graph, termed as Resource Description Framework (RDF) Graph. These graphs are solely based on specific semantic web knowledge bases. Furthermore, we propose a new community detection algorithm based on spectral clustering, termed as RDF-SCA, to detect patterns and communities in RDF Graphs. Finally, we present findings obtained from firing an RDF graph using our proposed RDF-SCA community detection algorithm.

关键词： Resource description framework Semantics Knowledge based systems Ontologies detection algorithms Databases

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An Efficient Ellipse Detector Based On Region detection And Arc Pruning

An Efficient Ellipse Detector Based On Region Detection And ...

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IEEE International Conference on Image Processing

作者： Tian Xie Ruike Zhang Jingchao Liang Qi Jia Xin Fan Zhongxuan Luo International School of Information Science and Technology Dalian University of Technology Dalian China

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

Detecting ellipses accurately and efficiently for real-world images is crucial for various visual-based applications. Most existing methods employ detection strategies throughout images, while most time is spent on the non-ellipse region. Meanwhile, small ellipses are often miss-detected due to the low resolution and fixed parameters of detectors. In this paper, we proposed an effective ellipse detector benefiting from the region detection method, which provides a basic estimation on the region and size of ellipses. Then, a two-level arc pruning strategy is proposed to detect ellipses efficiently while limiting false-positive and false-negative results. Furthermore, for the pre-estimated region without detected ellipses, interpolation method is employed to enlarge the target region, which makes small and blur ellipses to be detected. Experimental results demonstrate that the proposed method achieves competitive accuracy compared with the state-of-the-art methods.

关键词： Detectors Transforms Interpolation Lips detection algorithms Robustness Fitting

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detection Algorithm Approximation in the Background Limited Mode

Detection Algorithm Approximation in the Background Limited ...

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International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon)

作者： V.A. Rogachev Military Space Academy named after A.F. Mozhaisky St. Petersburg Russian Federation

ISBN: (数字)9781728169514

ISBN: (纸本)9781728169521

The authors consider the synthesis of optimal unbiased detecting rule for optoelectronic systems in the background limited mode. It was demonstrated that an optimal detection algorithm requires rather complex analytic calculations which cannot be executed in a live situation. The authors define a simpler detection algorithm based on the ratio between quadratic statistics and having a constant threshold level.

关键词： detection algorithms TV Mathematical model Approximation algorithms Signal processing algorithms Industrial engineering Dispersion

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