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检索条件"主题词=Change detection algorithms"

共 1584 条记录，以下是271-280 订阅

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An automated change-detection algorithm for HTML documents based on semantic hierarchies

An automated change-detection algorithm for HTML documents b...

引用

International Conference on Data Engineering

作者： Seung-Jin Lim Yiu-Kai Ng Computer Science Department Brigham Young University Provo UT USA

ISBN: (纸本)0769510019

The data at many Web sites is changing rapidly, and a significant amount of this data is presented in HTML documents that consist of markups and data contents. Although XML is becoming more popular for data exchange, the presentation of data contained in XML documents is given, by and large, in the HTML format using XSL(T). Since HTML was designed to "display" data from the human perspective, it is not trivial for a machine to detect (hierarchical) changes of data in an HTML document. In this paper, we propose a heuristic algorithm, called SCD (Semantic change detection), to detect semantic changes to the hierarchical data contents in any two HTML documents automatically. Semantic changes differ from syntactic changes since the latter refer to changes of data contents with respect to markup structures according to the HTML grammar. SCD does not require pre-processing, nor any knowledge of the internal structure of the source documents beforehand. The time complexity of SCD is O[(|X|/spl times/|Y|)log(|X|/spl times/|Y|)], where |X| and |Y| are the number of unique branches in the syntactic hierarchies of any two given HTML documents, respectively.

关键词： change detection algorithms HTML XML Eyes Computer science Humans Heuristic algorithms Displays Testing

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A Fast Non-Parametric Algorithm for Coherent change detection

A Fast Non-Parametric Algorithm for Coherent Change Detectio...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Giovanni Costa Andrea Monti Guarnieri Marco Manzoni Alessandro Parizzi DEIB Politecnico di Milano Milano MI TRE ALTAMIRA s.r.l. Milan Italy

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Developing algorithms to detect temporal and spatial changes in radar targets is paramount. This paper specifically addresses the temporal change detection aspect, introducing a rapid non-parametric Coherent change detection (CCD) algorithm named Fast-Permutational change detection (F-PCD). The F-PCD identifies temporal change Points (CPs) in a radar target by recognizing block structures in the coherence matrix, showing great robustness against non-stationary noise sources that generally affect the performance of the standard approaches. Moreover, the F-PCD is characterized by an accelerated inference process, ensuring efficiency without substantial performance loss. The F-PCD algorithm can be applied to different scenarios, for example, where DEM changes happen, e.g., mining sites, volcano eruptions, and earthquakes. For this reason, an example of the F-PCD application on an active open-pit mining site is presented to validate its effectiveness. Moreover, its generalization capability is demonstrated by a multi frequency-geometry analysis conducted on the same mining site. Finally, fully exploiting the F-PCD outcomes contributes to a broader understanding of temporal changes in SAR data and introduces new perspectives for interpreting InSAR datasets.

关键词： Geometry Technological innovation change detection algorithms Noise Radar Coherence Robustness

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A qualitative approach to the change detection problem with different types of sampling

A qualitative approach to the change detection problem with ...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： D. Pomorski M. Sbai M. Staroswiecki L.A.I.L.-URA 1440 Bât. P2 Université des Sciences et Technologies de Lille Villeneuve d'Ascq France Laboratoire d'Electronique et Systèmes Faculté des Sciences Université Mohammed 1er Oujda Morocco

In this paper, we are interested in nonstationary processes. We propose a method for change detection, based on a test of residual balance. We present some algorithms allowing one to take into account the different types of sampling procedures (simple, multiple, sequential, slippery) whose advantages and limits are underlined. The choice of the sampling type and of the size of samples is based on the calculation of wrong decision risks.

关键词： Sampling methods change detection algorithms Filtering Learning systems Artificial intelligence Decision trees System testing Atomic measurements Entropy Adaptive systems

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COSMO-SkyMed FOR UNSUPERVISED URBAN change detection USING RADAR BACKSCATTERING AND INTERFEROMETRIC COHERENCE

COSMO-SkyMed FOR UNSUPERVISED URBAN CHANGE DETECTION USING R...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Alessia Benedetti Matteo Picchiani Daniele Latini Fabio Del Frate Giovanni Schiavon Department of Civil Engineering and Computer Science Engineering University of Rome "Tor Vergata" Rome GEO-K s.r.l Rome Italy

In this paper a new approach based on the use of Synthetic Aperture Radar COSMO-SkyMed products to verify urban change detection and to observe new constructions is presented. SLC products information has been exploited, since the proposed procedure combines backscattering coefficient and coherence information as extracted from two interferometric data, acquired in a short time interval. The algorithm exploits the information from backscatter intensity and interferometric coherence. Firstly, the interferometric SAR couple is processed by an unsupervised Neural-Networks, particularly PCNN (Pulse Coupled Neural Network) is applied to create a preliminary changes map based on the difference of backscatter intensity information. Then, accuracy is further improved by the fusion with the coherence information. The achieved results shown as the combination of backscattering and coherence information, extracted from Very High Resolution SAR data, allows to provide very accurate urban change detections with a fast and unsupervised procedure. The latter is particularly suitable to process quickly huge amount of SAR data since its lower computational requirements with respect to e.g. supervised algorithms.

关键词： Coherence Backscatter Synthetic aperture radar Buildings Radar detection change detection algorithms

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Practical Considerations in Unsupervised change detection Using SAR Images

Practical Considerations in Unsupervised Change Detection Us...

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IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)

作者： Bulent Ayhan Chiman Kwan Applied Research LLC Rockville USA

ISBN: (纸本)9781728138862

change detection has a wide range of applications in hurricane damage assessment, urban growth monitoring, etc. It is well-known that synthetic aperture radar (SAR) can penetrate clouds and can work well under all weather conditions. However, SAR images also contain a lot of speckle noise that seriously affects change detection performance. In this paper, we focus on change detection using SAR images. In particular, we propose a new change detection algorithm that is applicable to both optical and SAR images. The detection performance of the algorithm was compared with a number of existing algorithms in the literature. Preliminary results using actual SAR images are encouraging. Most importantly, it was observed that effective change detection using SAR images require good denoising and post-processing algorithms in order to achieve decent performance.

关键词： geophysical image processing image denoising radar imaging remote sensing by radar speckle storms synthetic aperture radar Synthetic aperture radar Radar remote sensing Radar polarimetry Radar imaging Rescue image denoising Specific absorption rate SAFETY ANALYSIS REPORTS Speckle storms images processing algorithm change detection algorithms

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change detection and Object Segmentation: A Histogram of Features-Based Energy Minimization Approach

Change Detection and Object Segmentation: A Histogram of Fea...

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Indian Conference on Computer Vision, Graphics & Image Processing (ICVGIP)

作者： Nilanjan Ray Baidya Nath Saha Hong Zhang Department of Computing Science University of Alberta Canada

We consider here a change detection problem: to find regions of change on a test image with respect to a reference image. Unlike the state-of-the-art change detection and background subtraction algorithms that compute only local (pixel location-based) changes, we propose to minimize a novel region-based energy functional based on Bhattacharya coefficient involving histograms of image features. The optimization of the proposed energy functional simply consists of two very efficient searches if a crude segmentation such as a bounding box around the region of change is sufficient. Also, it allows variational optimization via level set-based curve evolution for supervised binary image labeling. The framework is demonstrated to cope well with considerable camera motion and shifts of objects between the test and the reference images. We illustrate encouraging results on finding bounding box around abnormality from brain MRI, object detection for maritime surveillance, and segmenting oil-sand particles from conveyor belt images.

关键词： Object detection Object segmentation Histograms Testing Image segmentation change detection algorithms Pixel Labeling Cameras Magnetic resonance imaging

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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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Online Graph-Based change Point detection in Multiband Image Sequences

Online Graph-Based Change Point Detection in Multiband Image...

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European Signal Processing Conference (EUSIPCO)

作者： R. A. Borsoi C. Richard A. Ferrari J. Chen J. C. M. Bermudez Université Côte d’Azur CNRS OCA Nice France Federal University of Santa Catarina Florianópolis Brazil Northwestern Polytechnical University Xi’an China Catholic University of Pelotas Pelotas Brazil

ISBN: (数字)9789082797053

ISBN: (纸本)9781728150017

The automatic detection of changes or anomalies between multispectral and hyperspectral images collected at different time instants is an active and challenging research topic. To effectively perform change-point detection in multitemporal images, it is important to devise techniques that are computationally efficient for processing large datasets, and that do not require knowledge about the nature of the changes. In this paper, we introduce a novel online framework for detecting changes in multitemporal remote sensing images. Acting on neighboring spectra as adjacent vertices in a graph, this algorithm focuses on anomalies concurrently activating groups of vertices corresponding to compact, well-connected and spectrally homogeneous image regions. It fully benefits from recent advances in graph signal processing to exploit the characteristics of the data that lie on irregular supports. Moreover, the graph is estimated directly from the images using superpixel decomposition algorithms. The learning algorithm is scalable in the sense that it is efficient and spatially distributed. Experiments illustrate the detection and localization performance of the method.

关键词： change detection algorithms Signal processing algorithms Europe Signal processing Computational efficiency Image sequences Hyperspectral imaging

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Requirements and techniques for an automated change detection system

Requirements and techniques for an automated change detectio...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： X. Dai S. Khorram Center for Earth Observation North Carolina State University Raleigh NC USA

To enhance the ability of remote sensing system to provide accurate, timely, and complete geospatial information at regional and/or global scale, an automated change detection system has been and will continue to be one of the important yet challenging problems in remote sensing. This research was designed to evaluate the requirements and prototype the algorithms for an automated change detection system at landscape level using various geospatial data sources including multisensor remotely sensed imagery and ancillary data layers. In this paper, the requirements for an operational change information extraction system and its associated techniques are discussed. These techniques are included in three subsystems: automated computer image understanding, multisource data fusion, and database updating and visualization.

关键词： Remote sensing Data mining Image databases Radar detection Testing Earth Algorithm design and analysis Prototypes change detection algorithms Visual databases

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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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