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检索条件"主题词=Detection Algorithms"

共 7403 条记录，以下是61-70 订阅

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Performance Effects of Dynamic Graph Data Structures in Community detection algorithms

Performance Effects of Dynamic Graph Data Structures in Comm...

引用

IEEE High Performance Extreme Computing Conference (HPEC)

作者： Thankachan, Rohit Varkey Swenson, Brian P. Fairbanks, James P. Georgia Inst Technol Sch Comp Sci Atlanta GA 30332 USA Georgia Tech Res Inst Atlanta GA 30332 USA

ISBN: (纸本)9781538659892

Community detection algorithms create a dynamic graph as an internal data structure for tracking agglomerative merges. This community (block) graph is modified heavily through operations derived from moving vertices between candidate communities. We study the problem of choosing the optimal graph representation for this data structure and analyze the performance implications theoretically and empirically. These costs are analyzed in the context of Peixoto's Markov Chain Monte Carlo algorithm for stochastic block model inference, but apply to agglomerative hierarchical community detection algorithms more broadly. This cost model allows for evaluating data structures for implementing this algorithm and we identify inherent properties of the algorithm that exclude certain optimizations.

关键词： Data structures detection algorithms Image edge detection Heuristic algorithms Sparse matrices Proposals Partitioning algorithms

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Detecting and Diagnosing Anomalous Behavior in Large Systems with Change detection algorithms

Detecting and Diagnosing Anomalous Behavior in Large Systems...

引用

IEEE International Conference on Software Reliability Engineering Workshops (ISSRE Wksp)

作者： Veena Mendiratta Zhuoran Liu Mrinmoy Bhattacharjee Yu Zhou Nokia Bell Labs Naperville IL USA Nokia Naperville IL USA

Large telecommunications networks are designed to achieve high reliability with hardware and software redundancy that is managed through complex fault-tolerant mechanisms for error detection and recovery. Because of the fault tolerant mechanisms, when errors do occur they do not always cause failures and, hence, it can be difficult to detect anomalous behavior of the system and to determine its root cause. In this paper, using sequential system performance data, we present the application of multivariate change detection algorithms and visual analytics methods for detecting and diagnosing anomalous behavior with low latency in telecommunications systems. Such methods, coupled with domain knowledge, are efficient and effective for detecting and diagnosing anomalies as compared to log analysis. We demonstrate our methods with real data from a large system.

关键词： detection algorithms Correlation Bayes methods Data analysis Cost function Telecommunications Time series analysis

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Research on Liveness detection algorithms Based on Deep Learning

Research on Liveness Detection Algorithms Based on Deep Lear...

引用

IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Ying Fan Yilin Shi Xianliang Wang Haiyang Yi Administration Residency Research Center of the Ministry of public security PRC Beijing China Beijing Hisign. Crop. Ltd. Beijing China

ISBN: (数字)9781728109459

ISBN: (纸本)9781728109466

Face liveness detection is designed to prevent the face recognition system from using the attacking image as the user's real image. At present, although there are many liveness detection methods, most of the methods have poor generalization ability in practical application. Because these methods are based on datasets, and these data cannot well simulate the data distribution in the real environment. In order to improve the generalization ability of the model, in this paper, we build model using the deep neural network and the dataset collected by ourselves. The experimental results show that our model has achieved significant improvement in the realistic scenario.

关键词： Face Face recognition Feature extraction Data models Convolution detection algorithms Deep learning

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Performance Evaluation of Community detection algorithms Based on Relationship Strength Measurement 10

Performance Evaluation of Community Detection Algorithms Bas...

引用

10th International Conference on Ubiquitous and Future Networks (ICUFN)

作者： Behera, Soom Lu, Haoye Nayak, Amiya Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON Canada

ISBN: (纸本)9781538646465

The study and analysis of networks have been a significant field of research as it holds its roots in varied disciplines like Biology, Chemistry, Sociology, Computer Applications and many more. Human beings have ventured into the era of a network with the rise of all kinds of networks such as the Internet and Social networks. detection of community structure in real networks is vital in terms of both theoretical and practical value. Many community detection methods are derived from specific backgrounds and their reliability is still questionable. Researchers hardly focus on the general definition of communities and the general community detection algorithms. The discrepancy between the two might pose some obstacles to the optimization of them so that it is hard to use one algorithm to perfect the other. Recently, Lu et al. [1] have proposed a general method for constructing network model from the real-world problem. Also, they have given a general definition of community structure as well as a complete procedure for detecting communities. In this paper, we apply the efficient resistance distance function [2] on Lu et al.'s algorithm and compare its performance with other community detection algorithms that allow for overlaps.

关键词： detection algorithms Resistance Measurement Social network services Greedy algorithms Biology Network topology"

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Review and Comparison of QRS detection algorithms for Arrhythmia Diagnosis

Review and Comparison of QRS Detection Algorithms for Arrhyt...

引用

IEEE International Conference on Signal Processing, Computing and Control (ISPCC)

作者： Kirti Harsh Sohal Shruti Jain Jaypee University of Information Technology Solan H.P India

ISBN: (纸本)9781728139890

The electrocardiogram is the graphical representation of the bio potential generated by the movement of the heart and is used to diagnose different types of heart diseases. The main purpose is to compute Heart Rate and RR interval using QRS complex detection algorithm. Several algorithms for QRS complex detection have been discussed on the basis of pre-processing and decision making stages. Evaluation of these algorithms is supported on the basis of different performance parameters such as sensitivity and positive predictive rate. After reviewing different papers, authors came across Entropy based wavelet transform, which gives better performance for QRS detection. The implementation of an existing algorithm on different ECG databases is done. Further QRS based heart diseases were discussed based on Heart Rate and RR intervals.

关键词： Electrocardiogram QRS complex Arrhythmia Heart Rate QRS complex Electrocardiography Heart Rate Cardiac Arrhythmias Heart Diseases detection algorithms RR interval Vital Signs characteristic parameter algorithms

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IMPROVEMENT OF DEFORESTATION detection algorithms USED IN JJ-FAST

IMPROVEMENT OF DEFORESTATION DETECTION ALGORITHMS USED IN JJ...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Manabu Watanabe Christian Koyama Masato Hayashi Izumi Nagatani Takeo Tadono Masanobu Shimada Tokyo Denki University JAXA

JJ-FAST is the first SAR-based global and early deforestation monitoring system, and started the operation from November 2016. In this paper, improved deforestation detection algorithm were suggested for using JJ-FAST system. One of the improvement is to increase maximum number of data used from 15 to 20 to suppress error detection occurred in mountain area and swamp forest. The other improvement is to adopt 0.5 dB lower threshold level to increase number of deforestation detection. Suggested algorithm were evaluated by using optical satellite data (GLAD), obtained in one of the active deforestation spots in Peru, Brazil, Cambodia, and Mozambique. User's accuracies increases by 6.7%, and number of correctly detected deforestation polygon make it 1.3 times as large.

关键词： Forestry detection algorithms Time series analysis Synthetic aperture radar Monitoring Remote sensing Satellites

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Community Deception or: How to Stop Fearing Community detection algorithms (Extended Abstract) 34

Community Deception or: How to Stop Fearing Community Detect...

引用

34th IEEE International Conference on Data Engineering Workshops (ICDEW)

作者： Fionda, Valeria Pirro, Giuseppe Univ Calabria Dept Math & Comp Sci Arcavacata Di Rende Italy CNR ICAR Arcavacata Di Rende Italy

ISBN: (纸本)9781538655207

Community deception is the problem of hiding a community from community detection algorithms. This is an important task whenever a group (e.g., activists, police enforcements) want to observe and cooperate in a social network while avoiding to be detected. We formalize the community deception problem and propose an efficient algorithm, based on the concept of community safeness, which allows to achieve deception by carefully identifying and rewiring a certain number of the community members' connections. Deception can be practically achieved in social networks like Facebook or Twitter by friending (following) or unfriending (unfollowing) network members. We validated our approach and compared it with related research on a variety of (large) real networks with encouraging results.

关键词： detection algorithms Image edge detection Knowledge engineering Electronic mail Law enforcement Facebook

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The detection algorithms for Similar Duplicate Data

The Detection Algorithms for Similar Duplicate Data

引用

International Conference on Systems and Informatics (ICSAI)

作者： Jin-yu Song Quan Yu Ruo-yu Bao College of Command and Control Engineering Army Engineering University of PLA Nanjing China

ISBN: (数字)9781728152561

ISBN: (纸本)9781728152578

This paper studied and analyzed three algorithms which can be used to detect similar duplicate data records. Among them, the two commonly used duplicate data detection algorithms are basic sorted-neighborhood method (SNM) and priority queue algorithm. Both of them are based on sorting-merger thought. The third one is Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The paper also discussed some key problems in the application and implementation of algorithms, including how to choose the attributes of data records and calculate the similarity between these attributes of two records, the choice of the sort algorithm, the setting of sliding window size and queue length. The paper realized three algorithms by programming based on Matlab platform, as well as some technologies related to algorithms. The paper verified related conclusions and evaluated three algorithms by testing a lot of loaded data sets. The paper finally provided the instruction to apply these algorithms.

关键词： Clustering algorithms Sorting detection algorithms Eigenvalues and eigenfunctions Shape Measurement Data integrity

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Fairness across Network Positions in Cyberbullying detection algorithms

Fairness across Network Positions in Cyberbullying Detection...

引用

International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Vivek K. Singh Connor Hofenbitzer Rutgers University

ISBN: (数字)9781450368681

ISBN: (纸本)9781450368681

Cyberbullying, which often has a deeply negative impact on the victim, has grown as a serious issue in online social networks. Recently, researchers have created automated machine learning algorithms to detect Cyberbullying using social and textual features. However, the very algorithms that are intended to fight off one threat (cyberbullying) may inadvertently be falling prey to another important threat (bias of the automatic detection algorithms). This is exacerbated by the fact that while the current literature on algorithmic fairness has multiple empirical results, metrics, and algorithms for countering bias across immediately observable demographic characteristics (e.g. age, race, gender), there have been no efforts at empirically quantifying the variation in algorithmic performance based on the network role or position of individuals. We audit an existing cyberbullying algorithm using Twitter data for disparity in detection performance based on the network centrality of the potential victim and then demonstrate how this disparity can be countered using an Equalized Odds postprocessing technique. The results pave the way for more accurate and fair cyberbullying detection algorithms.

关键词： Measurement Prediction algorithms Machine learning algorithms detection algorithms Social network services Receivers Feature extraction

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Robust Sound detection & Localization algorithms for Robotics Applications

Robust Sound Detection & Localization Algorithms for Robotic...

引用

AIAA Science and Technology (SciTech) Forum and Exposition

作者： Ramadan, Mohammad Younes, Ahmad Bani Moheidat, Jafar San Diego State Univ Aerosp Engn Dept Univ Calif San Diego Joint Doctoral Program San Diego CA 92182 USA San Diego State Univ Dept Aerosp Engn San Diego CA 92182 USA Yarmouk Univ Elect Engn Irbid Jordan

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

algorithms for sound detection and localization are discussed. These algorithms are good fit for real-world scenarios as less assumptions are used, with no big extra add-up in complexity. The algorithms are presented in a way that can be easily programmed and implemented. The event detection algorithm is based on a probability approach that reduces the effect of the noisy features. The localization algorithm is a combination of the delay-and-sum (DAS) algorithm with the cross-correlation (CC) in a way that ensures high robustness. These algorithms are implemented on a microphone phased-array system attached to a quadcopter that is able to detect and localize sound events successfully even with the existence of high propellers noise.

关键词： Acoustic detection algorithms Noise Microphone Device Component Road detection algorithms robotics

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