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检索条件"主题词=change detection algorithms"

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The ST6 autonomous sciencecraft experiment

The ST6 autonomous sciencecraft experiment

引用

IEEE Conference on Aerospace

作者： R. Sherwood S. Chien D. Tran B. Cichy R. Castano A. Davies G. Rabideau Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

The autonomous sciencecraft experiment (ASE), part of the new millennium space technology 6 project, is flying onboard the Earth Orbiter 1 (EO-1) mission. The ASE software enables EO-1 to autonomously detect and respond to science events such as: volcanic activity, flooding, and water freeze/thaw. ASE uses classification algorithms to analyze imagery onboard to detect change and science events. detection of these events is then used to trigger follow-up imagery. Onboard mission planning software then develops a response plan that accounts for target visibility and operations constraints. This plan is then executed using a task execution system that can deal with run-time anomalies. In this paper, we describe the autonomy flight software and how it enables a new paradigm of autonomous science and mission operations. We also describe our approach to testing and validation the ASE software, how we prepared the ASE software for space flight, and the current experiment status and future plans.

关键词： Event detection Space technology Geoscience Volcanic activity Floods change detection algorithms Classification algorithms Image analysis Algorithm design and analysis Runtime

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Effectively Maintaining Single View Consistency in Web Warehouses

Effectively Maintaining Single View Consistency in Web Wareh...

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International Conference on Computer and Information Technology (CIT)

作者： Yan Zhang Xiangdong Qin Center for Information Sciences Peking University Beijing China Department of Science and Technology Hebei University Baoding China

ISBN: (纸本)076952432X

Web warehouse provides high availability and efficiency by utilizing materialized Webviews, which should be refreshed in time to keep freshness. During the refreshing, the consistency between a Webview and its base data, which is formally named single view consistency (abbreviated as SVC), must be guaranteed. Since the base data changes in a Web warehousing environment do not propagate from data sources to the information consumers, which is far different from the case in the traditional data warehouses, we must pursue new maintenance methods. In this paper we first introduce the definition for SVC, and then we present an algorithm RCA to keep SVC as well as an effective base data change detection method SAA. We illustrate that RCA and SAA can guarantee SVC and they are effective in the Web environment

关键词： Static VAr compensators Warehousing Data warehouses Service oriented architecture Materials science and technology Availability change detection algorithms Web sites Information analysis Decision support systems

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Improved watershed segmentation algorithm for high resolution remote sensing images using texture

Improved watershed segmentation algorithm for high resolutio...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Ziyu Wang Cuiyu Song Zhongzhong Wu Xiuwan Chen Institute of Remote Sensing & GIS Peking University Beijing China Shandong University of Science and Technology China

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On the Effectiveness of multi-similarity for early detection of worms

On the Effectiveness of multi-similarity for early detection...

引用

IEEE International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)

作者： Hui He Mingzeng Hu Hongli Zhang Zhenjiang Tang School of Computer Science and Technology Harbin Institute of Technology China

In this paper, an effective algorithm for early detection of worms is proposed. The early detection algorithm based on multi-similarity integrates the worms’ behavior attributes with their traffic distribution and detects abnormal behavior by their similarity distribution change of some attributes. Three groups of experiments are conducted to evaluate the effectiveness of the algorithm. The results show that the multi-similarity owning the specialty of higher true positive, lower false positive and false negative. It can be conclude that the algorithm can detect the worm attack ahead of its overspreading on the large-scale network.

关键词： Computer worms change detection algorithms detection algorithms Large-scale systems Internet Stochastic processes Helium Computer science IP networks Explosives

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Protect e-commerce against DDoS attacks with improved D-WARD detection system

Protect e-commerce against DDoS attacks with improved D-WARD...

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IEEE International Conference on e-Technology, e-Commerce and e-Service

作者： Jian Kang Zhe Zhang Jiu-bin Ju Department of Computer Science & Technology Jilin University Changchun China

DDoS attack has caused severe damage to e-commerce and e-service and is great intimidation to the development of them. After analyzing the detection algorithm of D-WARD, a representative source-end DDoS detection system, we introduced a nonparametric change point detection method in statistics and improved D-WARD with nonparametric recursive CUSUM algorithm and compared their respective performance. Experiments proved that the improved system is lower in false-positive rate and false-negative rate, which is more accurate and could adapt to more complex network environments. This improved system could be utilized in the protection of e-commerce against DDoS attacks.

关键词： Protection Computer crime IP networks Computer science Electronic commerce Performance analysis Algorithm design and analysis detection algorithms Statistical analysis change detection algorithms

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Learning texture classifier for flooded region detection in SAR images

Learning texture classifier for flooded region detection in ...

引用

International Conference on Computer Graphics, Imaging and Visualization, CGIV

作者： Shiqing Zhang Hanqing Lu National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences China

In this paper a new texture-based change detection approach is proposed to identify the flooded regions in SAR images. The main novelty of our approach is that the most distinctive texture information is automatically learned from the training set. Forty texture features, which are extracted from a pair of bi-temporal SAR images, are used to construct the weak classifier pool. After AdaBoost training, a strong classifier is optimally combined by a small subset of the candidate weak classifiers. The experimental results demonstrate the effectiveness of the proposed approach.

关键词： Pixel Floods Feature extraction Data mining Synthetic aperture radar Lighting Radar detection change detection algorithms Laboratories Pattern recognition

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Vision system for decentralised wide area surveillance using multiple nodes

Vision system for decentralised wide area surveillance using...

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International Conference on Information Fusion

作者： R. Alexander G. Jones H. Knowles V. Leung G. Watson Advanced Technology Centre BAE Systems Bristol UK

In a decentralised wide area surveillance system (D-WASS), the two principal objectives are to first detect the events of interest reliably, and second to track the progression of these events and maintain a globally consistent track of the object for the extent of the camera fields of view. In this paper, we discuss an implementation of a 9-camera D-WASS with non-contiguous views, and analyse the performance of the tracking and vision sub-systems both empirically and analytically. In this application, event-based change detection algorithms in image space, as well as data association and tracking algorithms in a consistent real world coordinate system are realised in a real-time environment where both physical and temporal constraints are taken into consideration. This system has been demonstrated to work satisfactorily under various operating conditions. In order to characterise the performance of the system, the vision and tracking components, as well as the dependence of the latter on the former from a systems viewpoint, are studied analytically. The results are compared with those obtained empirically from real ground-truthed data. Potential extensions and improvements to the current implementation are also discussed.

关键词： Machine vision Surveillance Performance analysis Object detection Event detection Maintenance Cameras detection algorithms change detection algorithms Real time systems

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Dynamic learning of automata from the call stack log for anomaly detection

Dynamic learning of automata from the call stack log for ano...

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International Conference on Information Technology: Coding and Computing (ITCC)

作者： Zhen Liu S.M. Bridges Department of Computer Science and Engineering Mississippi State University USA

Anomaly detection based on monitoring of sequences of system calls has proved to be an effective approach for detection of previously unknown attacks on programs. This paper describes a new model for profiling normal program behavior that can be used to detect intrusions that change application execution flow. The model (hybrid push down automaton, HPDA) incorporates call stack information and can be learned by dynamic analysis of training data captured from the call stack log. The learning algorithm uses call stack information maintained by the program to build a finite state automaton. When compared to other approaches including VtPath which also uses call stack information, the HPDA model produces a more compact and general representation of control flow, handles recursion naturally, can be learned with less training data, and has a lower false positive rate when used for anomaly detection. In addition, dynamic learning can also be used to supplement a model acquired from static analysis.

关键词： Learning automata Training data Power system modeling Heuristic algorithms Bridges Computer science Computerized monitoring Data analysis Information analysis change detection algorithms

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Hybrid speaker-based segmentation system using model-level clustering

Hybrid speaker-based segmentation system using model-level c...

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

作者： Hyoung-Gook Kim D. Ertelt T. Sikora Communication Systems Institute Technical University Berlin Germany

We present a hybrid speaker-based segmentation, which combines metric-based and model-based techniques. Without a priori information about the number of speakers and speaker identities, the speech stream is segmented in three stages: (1) the most likely speaker changes are detected; (2) to group segments of identical speakers, a two-level clustering algorithm is performed using a Bayesian information criterion (BIC) and HMM model scores - every cluster is assumed to contain only one speaker; (3) the speaker models are reestimated from each cluster by HMM. Finally a resegmentation step performs a more refined segmentation using these speaker models. To measure the performance, we compare the segmentation results of the proposed hybrid method versus metric-based segmentation. Results show that the hybrid approach using two-level clustering significantly outperforms direct metric-based segmentation.

关键词： Hidden Markov models Speech Clustering algorithms Loudspeakers change detection algorithms Robust stability Feature extraction Merging Bayesian methods Algorithm design and analysis

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Coarse-to-fine strategy for robust and efficient change detectors

Coarse-to-fine strategy for robust and efficient change dete...

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： A. Bevilacqua L. Di Stefano A. Lanza ARCES-Department of Electronics Computer Science and Systems University of Bologna Bologna Italy

We present a novel approach to change detection based on a coarse-to-fine strategy. An efficient coarse-level detection is proposed that filters out most of the possible false changes, thus attaining reliable and tight coarse-grain super-masks of the truly changed areas. The subsequent fine-level detection can thus "focus the attention" just on the "interesting" parts of the frame and perform a robust selective background updating procedure by considering the complement of these masks. Besides, the analysis of a strip of pixels surrounding each coarse-grain blob allows to infer information on light changes possibly occurring in the blob's vicinity. Although any algorithm can be used as the final fine-level detection, here we show how the approach applies to a particular algorithm we devised, based on a non-parametric statistical modelling of the camera noise.

关键词： Robustness change detection algorithms Lighting Detectors Filters Strips Cameras Switches Computer science Information analysis

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