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检索条件"主题词=Detection algorithms"

共 7359 条记录，以下是161-170 订阅

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Performance Analysis of T-Wave-Offset detection algorithms on Patients with Cardiac Diseases

Performance Analysis of T-Wave-Offset Detection Algorithms o...

引用

Computers in Cardiology (CinC)

作者： Deborah Nairn Pietro Bonizzi Joël Karel Alfonso Aranda Medtronic Bakken Research Center Maastricht The Netherlands Department of Data Science and Knowledge Engineering Maastricht University The Netherlands

ISBN: (纸本)9781728109244

Cardiovascular diseases are the number one cause of death in the world. The application of automatic processing algorithms can provide important information about these heart diseases. However, the design of these algorithms can be challenging due to the morphological variations in ECG signals, specifically in the T-wave-offset. This study proposes a comparison of several T-offset detection algorithms on healthy subjects and patients suffering from cardiac diseases. Seven state of the art algorithms were selected for implementation and were evaluated using the same dataset and benchmark to provide a fair comparison. Although no algorithm performs with 100% accuracy for all patients, most can perform well with regards to the healthy patients, with two algorithms having a high performance, above 70% accuracy, on all patients.

关键词： Databases Electrocardiography Morphology Cardiac disease Heart Standards detection algorithms

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A framework for analyzing community detection algorithms

A framework for analyzing community detection algorithms

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IEEE Students' Technology Symposium (TechSym)

作者： Anupam Biswas Bhaskar Biswas Department of Computer Science & Engineering Indian Institute of Technology (BHU) Varanasi India

Evaluation of community detection algorithms is very important to ensure both accuracy and quality of identified communities. Measuring quality incorporates edges, while measuring accuracy involves node labels. Due to this fundamental difference between accuracy and quality, often the evaluation process confronts with the issues such as trade-off between the two. In addition, real world networks such as social networks are of unknown structure and complex. Accuracy of communities detected with any algorithm for these networks cannot be measured due to unavailability of ground truth. In such cases, the algorithms are certainly more likely to predict accurate communities that show higher inclination towards accuracy in the networks where ground truths are available. In this paper, a framework is proposed to analyze Relative Inclination Towards accuracy (RITA) of a set of community detection algorithms. The RITA analysis gives an intuition about how likely an algorithm would produce accurate communities in the networks where ground truth is not available. Moreover, the RITA analysis overcomes trade-off between accuracy and quality by incorporating both into a common platform. Results on variety of networks show the competency of proposed framework in dealing with the trade-off during analysis.

关键词： Measurement detection algorithms Algorithm design and analysis Dolphins Social network services Prediction algorithms Image edge detection

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Mitosis detection on histopathological images using statistical detection algorithms

Mitosis detection on histopathological images using statisti...

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IEEE Signal Processing and Communications Applications (SIU)

作者： Mustafa Üstüner Gökhan Bilgin Harita Mühendisliği Bölümü İstanbul Türkiye Bilgisayar Mühendisliği Bölümü Yıldız Teknik Üniversitesi İstanbul Türkiye

In this work, the utility and accuracy of the statistical detection algorithms for the detection of mitosis on histopathological images have been investigated. In the first stage, the subset images involving mitotic cells from the original images have been created. The occurance based texture filters have been applied to each subset image. Then the training/testing dataset has been created from these subset images. Later, the three statistical detection algorithms have been implemented in this work, namely matched filtering (MF), constrained energy minimization (CEM) and adaptive coherence estimator (ACE). The accuracies over 80% have been obtained for each method and four different evaluation measures have been utilized. The results indicate that the MF is the best algorithm on mitosis detection among the implemented algorithms.

关键词： Hyperspectral imaging Filtering Coherence detection algorithms Minimization

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A Literature Survey on Blur detection algorithms for Digital Imaging

A Literature Survey on Blur Detection Algorithms for Digital...

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International Conference on Artificial Intelligence, Modelling and Simulation (AIMS)

作者： Boon Tatt Koik Haidi Ibrahim School of Electrical & Electronic Engineering Engineering Campus Universiti Sains Malaysia Nibong Tebal Penang Malaysia

Development of blur detection algorithms has attracted many attentions in recent years. The blur detection algorithms are found very helpful in real life applications and therefore have been developed in various multimedia related research areas including image restoration, image enhancement, and image segmentation. These researches have helped us in compensating some unintentionally blurred images, resulted from out-of-focus objects, extreme light intensity, physical imperfection of camera lenses and motion blur distortion. Overview on a few blur detection methods will be presented in this paper. The methods covered in this manuscript are based on edge sharpness analysis, low depth of field (DOF) image segmentation, blind image de-convolution, Bayes discriminant function method, non-reference (NR) block, lowest directional high frequency energy (for motion blur detection) and wavelet-based histogram with Support Vector Machine (SVM). It is found that there are still a lot of future works need to be done in developing an efficient blur detection algorithm.

关键词： Image edge detection Digital images Support vector machines Image restoration Image segmentation Histograms detection algorithms

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Performance Evaluation of State-of-the-Art Discrete Symmetry detection algorithms

Performance Evaluation of State-of-the-Art Discrete Symmetry...

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26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), vol.12

作者： Minwoo Park Seungkyu Lee Po-Chun Chen Somesh Kashyap Asad A. Butt Yanxi Liu Department of Computer Science and Engineering Department of Electrical Engineering The Pennsylvania State University USA

Symmetry is one of the important cues for human and machine perception of the world. For over three decades, automatic symmetry detection from images/patterns has been a standing topic in computer vision. We present a timely, systematic, and quantitative performance evaluation of three state of the art discrete symmetry detection algorithms. This evaluation scheme includes a set of carefully chosen synthetic and real images presenting justified, unambiguous single or multiple dominant symmetries, and a pair of well-defined success rates for validation. We make our 176 test images with associated hand-labeled ground truth publicly available with this paper. In addition, we explore the potential contribution of symmetry detection for object recognition by testing the symmetry detection algorithm on three publicly available object recognition image sets (PASCAL VOC'07, MSRC and Caltech-256). Our results indicate that even after several decades of effort, symmetry detection in real-world images remains a challenging, unsolved problem in computer vision. Meanwhile, we illustrate its future potential in object recognition.

关键词： detection algorithms Reflection Computer vision Testing Object detection Object recognition Image edge detection Detectors Image databases Computer science

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Nonolinear Transforms In Qrs detection algorithms

Nonolinear Transforms In Qrs Detection Algorithms

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

作者： S. Suppappola Ying Sun Department of Electrical Engineering University of Rhode Island Kingston RI USA

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Evaluating Real-Time Anomaly detection algorithms -- The Numenta Anomaly Benchmark

Evaluating Real-Time Anomaly Detection Algorithms -- The Num...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Alexander Lavin Subutai Ahmad Numenta Inc. Redwood City CA

Much of the world's data is streaming, time-series data, where anomalies give significant information in critical situations, examples abound in domains such as finance, IT, security, medical, and energy. Yet detecting anomalies in streaming data is a difficult task, requiring detectors to process data in real-time, not batches, and learn while simultaneously making predictions. There are no benchmarks to adequately test and score the efficacy of real-time anomaly detectors. Here we propose the Numenta Anomaly Benchmark (NAB), which attempts to provide a controlled and repeatable environment of open-source tools to test and measure anomaly detection algorithms on streaming data. The perfect detector would detect all anomalies as soon as possible, trigger no false alarms, work with real-world time-series data across a variety of domains, and automatically adapt to changing statistics. Rewarding these characteristics is formalized in NAB, using a scoring algorithm designed for streaming data. NAB evaluates detectors on a benchmark dataset with labeled, real-world time-series data. We present these components, and give results and analyses for several open source, commercially-used algorithms. The goal for NAB is to provide a standard, open source framework with which the research community can compare and evaluate different algorithms for detecting anomalies in streaming data.

关键词： Detectors Real-time systems Benchmark testing Measurement detection algorithms Standards Algorithm design and analysis

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Collection of pediatric ECG data for testing detection algorithms in Automated External Defibrillators

Collection of pediatric ECG data for testing detection algor...

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Computers in Cardiology (CinC)

作者： Patricia Radon Gero von Wagner Norbert Kraft Uwe Steinhoff Physikalisch-Technisch Bundesanstalt Berlin Germany Metrax GmbH Rottweil Germany

ISBN: (纸本)9781467320764

Arrhythmia detection algorithms in Automated External Defibrillators (AEDs) need a special approval for use in children aged 0-8 years. Our aim is to establish a pediatric ECG reference dataset with rhythm annotations for the assessment of arrhythmia detection algorithms of AEDs. The database will consist of a training dataset with a public interface for end-users to optimize their algorithms and an independent validation data set that remains hidden. Currently we collected and analyzed 534 pediatric ECGs with non-shockable heart rhythms. We characterized the signal automatically by estimating noise level, power line interferences and movement artifacts. Also RR intervals and extrasystoles are automatically annotated. In combination with additional clinical annotations the pediatric ECG dataset provides an instrument for the development and assessment of AED algorithms for arrhythmia detection in children.

关键词： Electrocardiography Databases Pediatrics Rhythm detection algorithms Noise Guidelines

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Channel estimation and data detection algorithms for UWB multiuser communications

Channel estimation and data detection algorithms for UWB mul...

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International Symposium on Wireless Pervasive Computing (ISWPC)

作者： Alessandro Barbieri Fabrizio Pancaldi Giorgio M. Vitetta Department of Information Engineering University of Modena and Reggio Emilia and INFM Modena Italy Department of Science and Methods for Engineering University of Modena and Reggio Emilia and INFM Reggio Emilia Italy

ISBN: (纸本)9781424468553;9781424468584

In this paper, a novel ultrawideband system for multiuser data communications is proposed. At the transmit side multiple users are allowed to send pulse position modulated signals in a synchronized fashion exploiting a given frequency subband in the same time intervals. Overlapped data frames sent by distinct users include low data rate training sequences with different repetition periods. This transmission strategy, known as rate division multiple access in the technical literature, allows to ease the first two fundamental tasks at the receive side, namely joint channel estimation and timing synchronization. Channel estimates are exploited by a multiuser detector based on the Viterbi algorithm and separating the contribution generated by the user of interest from those produced by all the other co-channel users. Numerical results evidence that the proposed solution can offer an efficient usage of the available spectrum at the price of a limited complexity.

关键词： Channel estimation detection algorithms Pulse modulation Data engineering Frequency synchronization Multiple access interference Ultra wideband technology Viterbi algorithm Payloads Pervasive computing

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Image Copy-Move Forgery detection algorithms Based on Spatial Feature Domain

Image Copy-Move Forgery Detection Algorithms Based on Spatia...

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International Colloquium on Signal Processing & Its Applications, CSPA

作者： Ismail Taha Ahmed Baraa Tareq Hammad Norziana Jamil College of Computer Sciences and Information Technology University of Anbar Anbar Iraq College of Computing and Informatics Universiti Tenaga Nasional Malaysia

ISBN: (数字)9781665414845

ISBN: (纸本)9781665430593

Currently, digital image forgery (DIF) become more active due to the advent of powerful image processing tools. On a daily, many images are exchanged through the internet, which makes them susceptible to such effects. One of the most popular of the passive image forgery techniques is copy-move forgery. In the Copy-move forgery, the basic process is copy/paste from one area to another in the same image. In this paper, the proposed image copy-move forgery detection (IC-MFDs) involves five stages: image preprocessing, dividing the image into overlapping blocks, calculating the mean and standard deviation of each block, feature vectors are then sorted lexicographically, then feeding the feature vector to the Support Vector Machine (SVM) classifier to identify the image as authentic or forged. Experiments are performed on a standard dataset of copy move forged images MICC-F220 to evaluate the proposed technique. The findings indicate that the proposed IC-MFDs can be extremely accurate in terms of detection Accuracy (98.44). We also compare some state-of-the-art approaches with our proposed IC-MFDs. It's noted that the findings obtained are better than these approaches.

关键词： Splicing Support vector machine classification Tools Feature extraction Forgery detection algorithms Standards

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