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检索条件"主题词=Change detection algorithms"

共 1587 条记录，以下是281-290 订阅

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A High Performance CPU-GPU Algorithm for change detection in Satellite Images Using Singular Values and Data Mining Techniques

A High Performance CPU-GPU Algorithm for Change Detection in...

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International Conference on Computational Science and Computational Intelligence (CSCI)

作者： Quoc-Nam Tran A. Aafaque Southeastern LA University USA

ISBN: (纸本)9781728113616

We present a high performance hybrid method for unsupervised change detection in multi-temporal satellite images using singular values and clustering, an important problem for satellite image processing. We partition the difference image into small data blocks with non-overlapping and overlapping pixels and use these data blocks to justify the changing status of the contents. However, instead of building an eigen space from the orthonormal eigenvectors extracted through Principal Component Analysis (PCA) of the data blocks, we analyze the singular values and use only a small subset of the values. This eigen space with much smaller number of dimensions helped to significantly improve the efficiency of the change detection algorithm. The change detection is achieved by partitioning the feature vector space into two clusters using clustering algorithms. We utilize the designs of scalable and efficient parallel algorithms for many-core GPU devices using CUDA. Our algorithms expose substantial fine-grained parallelism while maintaining minimal global communication. Experimental results using real-world satellite images showed that our algorithm works efficiently with real world satellite images. We also tested our algorithm under different noise conditions and found that it is stable and accurate.

关键词： Satellites change detection algorithms Clustering algorithms Feature extraction Covariance matrices Principal component analysis Data mining

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The modified CUSUM algorithm for slow and drastic change detection in general HMMs with unknown change parameters

The modified CUSUM algorithm for slow and drastic change det...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： N. Vaswani ECE Department Georgia Institute of Technology Atlanta GA USA

We study the change detection problem in a general HMM when the change parameters are unknown and the change can be slow or drastic. Drastic changes can be detected easily using the increase in tracking error or the negative log of observation likelihood (OL). But slow changes usually get missed. We have proposed in past work a statistic called ELL which works for slow change detection. Now single time estimates of any statistic can be noisy. Hence we propose a modification of the cumulative sum (CUSUM) algorithm which can be applied to ELL and OL and thus improves both slow and drastic change detection performance.

关键词： change detection algorithms Hidden Markov models Statistics Fault detection State estimation Context modeling Probability distribution Linear systems Nonlinear systems Quality control

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Efficient change detection for high dimensional data streams

Efficient change detection for high dimensional data streams

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IEEE International Conference on Big Data

作者： Spiros V. Georgakopoulos Sotiris K. Tasoulis Vassilis P. Plagianakos Department of Computer Science and Biomedical Informatics University of Thessaly Lamia Greece Department of Applied Mathematics Liverpool John Moores University Liverpool United Kingdom

The recent technological advancements in cloud computing and the access in increasing computational power has led in undertaking the data processing derived by mobile devices. In particular, when these data are high dimensional this is indispensable, since the mobile device has to balance its processing functionalities to additional services. However, developing efficient algorithms could allow various types of analysis to be performed locally, avoiding the necessity of a constantly connected device. In this work, we present a methodology that combines lightweight dimensionality reduction and change detection techniques. The experimental results justify its impressive performance and subsequently its usefulness in several tasks.

关键词： Principal component analysis Legged locomotion Time series analysis change detection algorithms Data processing Mobile handsets Algorithm design and analysis

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Performance evaluation of an online load change detection algorithm

Performance evaluation of an online load change detection al...

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International Conference on Computer and Automation Engineering, ICCAE

作者： Felipe Mata Javier Aracil Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain

ISBN: (纸本)9781424455690

In this paper we evaluate an online load change detection algorithm, aimed to identify changes in traffic loads when monitoring Internet links. This online change detector was first introduced in [1] and produces an alert when a sustained and statistically significant change has been detected. Then, the network manager verifies the change and takes action if the change is truly relevant. We show that the behavior of the algorithm with synthetically generated time series is appropriate, and the obtained results are as expected.

关键词： detection algorithms change detection algorithms Detectors Testing Statistical analysis Telecommunication traffic Monitoring Internet Clustering algorithms Piecewise linear techniques

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Wavechange: a Procedure for change detection Based on Wavelet Product Spaces

Wavechange: a Procedure for Change Detection Based on Wavele...

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International Workshop on the Analysis of Multi-temporal Remote Sensing Images (MultiTemp)

作者： Luis M.T. de Carvalho Fausto W. Acerbi Jose R. Scolforo Jose M. de Mello Antonio D. de Oliveira Federal University of Lavras Lavras Brazil

Our objective was to develop a procedure for change detection which is less sensitive to problems caused by misregistration, atmospheric effects and variations in vegetation phenology. The procedure is based on redundant wavelet transforms. Wavelet correlation was explored by taking point wise products of adjacent scales in order to enhance coefficients due to changes and smooth out noises. Local maxima were detected on the product spaces at varying spatial resolutions. The detected maxima were used as seeds for a multiscale region growing algorithm. The results showed that the method is not sensitive to geometric and radiometric misregistrations because of the multiresolution approach to feature extraction.

关键词： Radiometry Vegetation mapping Image analysis Atmospheric waves change detection algorithms Noise reduction Object detection Spatial resolution Earth Image sensors

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A novel approach to scene change detection using a cross entropy

A novel approach to scene change detection using a cross ent...

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IEEE International Conference on Image Processing

作者： Sang Hyun Kim Rae-Hong Park Department of Electronic Engineering Sogang University Seoul South Korea

In huge video databases, an effective video indexing method is required. While manual indexing is the most effective approach to this goal, it is slow and expensive. Thus automatic indexing is desirable, and previously various indexing tools for video databases have been developed. For efficient video indexing and retrieval, the similarity measure is an important factor. This paper presents new similarity measures between frames and proposes a new algorithm to detect scene changes using a cross entropy defined between two histograms. Experimental results show that the proposed algorithm is fast and effective compared with several conventional algorithms to detect abrupt scene changes and gradual transitions including fade in/out and flash light scenes.

关键词： Layout Entropy Histograms Video compression Indexing Cameras Gunshot detection systems Image databases Image segmentation change detection algorithms

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Estimation and change detection of tire-road friction using the wheel slip

Estimation and change detection of tire-road friction using ...

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IEEE International Symposium on Computer Aided Control System Design (CACSD)

作者： F. Gustafsson Department of Electrical Engineering Linköping University Linkoping Sweden

This paper describes some filtering and change detection problems in an approach to estimate the tire-road friction. The method is aimed to work during a normal drive using information from standard sensors only, and the driver is informed about the maximal friction force and warned for sudden changes. From a physical model of tire-road friction based on the so called wheel slip, a Kalman filter is constructed. To get a fast response to friction changes, some alternative change detectors are examined. We also describe the algorithm that has been implemented in real-time on a Volvo 850 and some of the results from extensive tests.

关键词： Friction Wheels Testing Tires Filtering change detection algorithms Road vehicles Intelligent vehicles Road safety Intelligent sensors

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Sequential Sparsification for change detection

Sequential Sparsification for Change Detection

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26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), vol.4

作者： Necmiye Ozay Mario Sznaier Octavia I. Camps Department of Electrical and Computer Engineering Northeastern University Boston MA USA

This paper presents a general method for segmenting a vector valued sequence into an unknown number of sub-sequences where all data points from a subsequence can be represented with the same affine parametric model. The idea is to cluster the data into the minimum number of such subsequences which, as we show, can be cast as a sparse signal recovery problem by exploiting the temporal correlation between consecutive data points. We try to maximize the sparsity (i.e. the number of zero elements) of the first order differences of the sequence of parameter vectors. Each non-zero element in the first order difference sequence corresponds to a change. A weighted l{sub}1 norm based convex approximation is adopted to solve the change detection problem. We apply the proposed method to video segmentation and temporal segmentation of dynamic textures.

关键词： Image segmentation Switches Noise robustness change detection algorithms Computer vision Image edge detection Data engineering Parametric statistics Noise level Pixel

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Online network performance degradation localization using probabilistic inference and change detection

Online network performance degradation localization using pr...

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IEEE Symposium on Network Operations and Management

作者： Andreas Johnsson Catalin Meirosu Christofer Flinta Research Area Packet Technologies Ericsson Research Kista Sweden

Detecting and localizing performance degradations is a difficult problem that increases in importance as telecom network transition to all-packet equipment. Operators require solutions that are accurate in localization and do not impose large additional costs in terms of hardware deployment or manual labor for operations. Existing commercial solutions are generally difficult to operate, while many academic proposals typically require significant computational resources and are difficult to adapt to production networks. This paper describes a novel network fault localization algorithm based on active network measurements, probabilistic inference and change detection. The algorithm is computationally efficient for networks with thousands of nodes and requires few configuration parameters. Results obtained in a simulated environment on tree topologies show that the solution provides fast and accurate localization of performance degradations.

关键词： Degradation Atmospheric measurements Particle measurements Network topology Time measurement Loss measurement change detection algorithms

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A New Time Series change detection Method for Landsat Land use and Land Cover change

A New Time Series Change Detection Method for Landsat Land u...

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International Workshop on the Analysis of Multi-temporal Remote Sensing Images (MultiTemp)

作者： Yukun Lin Lifu Zhang Nan Wang Institute of Remote Sensing and Digital Earth University of Chinese Academy of Sciences Beijing China Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing China

Time series change detection is an effective way of analyzing land use and land cover change (LULCC). However, producing accurate LULCC map is still challenging because of amplified false detections and high omission errors. Here, we proposed a new change detection method to reduce false detections while maintaining low omission errors. First, the time series is decomposed into three components in the temporal scale which is seasonal, linear trend and noise. The potential LULCC are detected in the seasonal component to keep a low omission rate. Second, the false alarm rate is reduced by combining the breakpoint information of all the spectral bands and the post-classification result. Finally, the information of neighboring pixels is utilized to reduce false alarm further. With Kansas City as the study sites, the results demonstrated the effectiveness and stability of the proposed approach. Our results will show the timing and location of LULCC for qualitative analysis. The results will also show that false detections are reduced significantly without compromising omission rate for quantitative analysis.

关键词： Remote sensing Time series analysis Earth Artificial satellites Market research change detection algorithms Classification algorithms

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