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检索条件"主题词=change detection algorithms"

共 1587 条记录，以下是561-570 订阅

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Illustration watermarks for vector graphics 11

Illustration watermarks for vector graphics

引用

11th Pacific Conference on Computer Graphics and Applications

作者： Sonnet, H Isenberg, T Dittmann, J Strothotte, T Otto Von Guericke Univ Dept Simulat & Graph Magdeburg Germany

ISBN: (纸本)0769520286

Digital watermarking is a technique for embedding information into data, such as images, 3D models, or audio files, such that some properties (i. e., security, imperceptibility, robustness) are maintained. While most of the existing watermarking techniques focus on encoding copyright information where security is one of the most important properties, we have developed algorithms for embedding Illustration Watermarks, i. e., content-related annotations for the image. Robustness against common media transformations, high capacity, and blind detection are our aspired properties while security and the usage of secure keys are less important. The medium that we are using for embedding data are 2D vector graphics. We introduce algorithms that change line attributes, introduce new vertices in certain patterns, and replace existing stroke segments by new lines in a stylistic way. Based on the modification they introduce, we categorize our techniques into whether they change the appearance of the image or not and whether the changes are perceivable by the naked eye or not. We demonstrate our techniques with silhouette lines obtained from 3D models. Such line drawings are a very common style utilized in many illustrations, in particular in the medical and technical domain.

关键词： Biomedical imaging change detection algorithms Computer graphics Data security Encoding Image segmentation Information security Robustness Steganography Watermarking

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Driver Intent Prediction with Barrier Functions

Driver Intent Prediction with Barrier Functions

引用

American Control Conference (ACC)

作者： Rahman, Yousaf Jankovic, Mrdjan Santillo, Mario Ford Motor Co Res & Adv Engn 2101 Village Rd Dearborn MI 48124 USA

ISBN: (纸本)9781665441971

Path planning and collision avoidance algorithms for driver assist systems and autonomous vehicles require predictions of the future locations of other vehicles. In the absence of V2X communication, driver intent prediction algorithms provide this information. Intent prediction algorithms generally fall into two categories: those based on vehicle dynamics models and filtering, and machine learning based approaches. Both approaches have advantages and drawbacks, but two disadvantages both approaches share is the relative computational complexity and the likelihood of false positives and negatives. In the literature, barrier functions (BF) are used to enhance safety by providing forward invariance of an admissible set. In this paper, BFs are used to determine driver intent in a comparatively efficient manner with quick detection particularly at high speeds, in a way where the chance of false positives and negatives can be significantly reduced.

关键词： Machine learning algorithms change detection algorithms Heuristic algorithms Prediction algorithms Path planning Safety Collision avoidance

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DETECTING LAND COVER change BY EVALUATING THE INTERNAL COVARIANCE MATRIX OF THE EXTENDED KALMAN FILTER

DETECTING LAND COVER CHANGE BY EVALUATING THE INTERNAL COVAR...

引用

IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Salmon, B. P. Kleynhans, W. van den Bergh, F. Olivier, J. C. Wessels, K. J. Univ Pretoria Dept Elect Elect & Comp Engn ZA-0002 Pretoria South Africa

ISBN: (纸本)9781467311595

In this paper, the internal operations of an Extended Kalman Filter is investigated to see if any useful information can be derived to detect land cover change in a MODIS time series. The Extended Kalman Filter expands its internal covariance if a significant change in reflectance value is observed, followed by adapting the state parameters to compensate for this change. The analysis shows a change detection accuracy above 90% can be attained when evaluating the elements within the internal covariance matrix to detect new human settlements, with a corresponding false alarm rate below 11%.

关键词： change detection algorithms Covariance matrix Kalman Filter Spatial information Time series analysis

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ESTABLISHING BASELINE INFORMATION ON AN ENHANCED COAL BED METHANE SITE WITH SPOT VGT-S10 AND ALOS PALSAR FOR SAFETY MONITORING

ESTABLISHING BASELINE INFORMATION ON AN ENHANCED COAL BED ME...

引用

IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Li, Xiaojing Ge, Linlin Hu, Zhe Cholathat, Rattanasuda Univ New S Wales Sch Surveying & Spatial Informat Syst Fac Engn Sydney NSW 2052 Australia

ISBN: (纸本)9781467311595

CO2 Enhanced Coal Bed Methane (ECBM) has been considered as one of the promising clean coal technologies to reduce green house gas emissions. Australia and China have begun a demonstrational project to explore the potential of ECBM in the gas/coal fields in Shanxi Province, China. A total of 12 ALOS PALSAR images and 354 SPOT VGT-S10 images have been successfully used to establish baseline information of ground deformation and vegetation dynamics on the site based on DInSAR and NDVI time series analysis respectively. Cross analysis between SOPT and MODIS has also been given. Such baseline information will play an important role in the future for monitoring environmental safety at the site.

关键词： change detection algorithms remote monitoring displacement measurements vegetation stress mapping NDVI

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A comparative study of QoS routing schemes that tolerate imprecise state information 11

A comparative study of QoS routing schemes that tolerate imp...

引用

11th International Conference on Computer Communications and Networks

作者： Yuan, X Zheng, W Ding, SL Florida State Univ Dept Comp Sci Tallahassee FL 32306 USA

ISBN: (纸本)078037553X

In large networks, maintaining precise global network state information is almost impossible. Many factors, including nonnegligible propagation delay, infrequent link state update due to overhead concerns, link state update policy, resource reservation, and hierarchical topology aggregation, have impacts on the precision of the global network state information. To achieve efficient Quality of Service (QoS) routing, a practical routing algorithm must be able to make effective routing decisions in the presence of imprecise global network state information. In this paper, we compare five QoS routing algorithms that were proposed to tolerate imprecise global network state information, safety-based routing, randontized routing, multi-path routing, localized routing, and static multi-path routing. The performance of these routing algorithms are evaluated under two link state update policies, the timer based policy and the threshold based policy. The strengths and limitations of each scheme are identified.

关键词： change detection algorithms Computer science Degradation Maintenance Network topology Probes Propagation delay Quality of service Routing

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Research of moving targets detection and identification

Research of moving targets detection and identification

引用

2nd Internationl Conference on Intelligent Computation Technology and Automation

作者： Jin Min Shi Lei Heilongjiang Inst Technol Dept Comp Sci & Technol Harbin 150050 Peoples R China

ISBN: (纸本)9780769538044

Accurate detection of moving targets is the main contents of researching for computer vision and image encoding, which has an extensive applicative prospect. The traditional dynamic template matching algorithm has the disadvantage when it detects the affine deformation target, it is easy to distinguish the target by mistake. For that reason, a novel improved dynamic template matching algorithm is proposed in this paper. Firstly, the improved temporal difference algorithm is used to detect the moving targets. Secondly, affine invariant moment is used as the invariable characteristic. Experimental results indicate that, compared with traditional dynamic template matching algorithm, our method has better detection performance.

关键词： Object detection Heuristic algorithms Image sequences Target recognition Computer vision Image coding change detection algorithms Image recognition Intelligent robots Automation

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Detecting changes in Streaming Data with Information-Theoretic Windowing 5

Detecting Changes in Streaming Data with Information-Theoret...

引用

IEEE International Conference on Big Data (IEEE Big Data)

作者： Kaneko, Ryoya Miyaguchi, Kohei Yamanishi, Kenji Univ Tokyo Grad Sch Informat Sci & Technol Tokyo Japan

ISBN: (纸本)9781538627150

This study addresses the problem of detecting change points in streaming data. Herein, we focus on detecting changes with low complexity and high accuracy to manage large-volume, high-velocity data. To this end, we propose a novel method of detecting changes via data compression, by introducing minimum description length (MDL) change statistics to an adaptive windowing regime. The time complexity of the resulting algorithm, Sequential Compression with Adaptive Windowing (SCAW), is optimal except for a logarithmic factor, and is theoretically justified through exponential upper bounds on error probabilities. Moreover, SCAW can be used to detect arbitrary types of changes by choosing an appropriate compressor. We also introduce the notion of asymptotic reliability as a criterion of change point detection algorithms, and determine SCAW's parameter using this criterion. Finally, we demonstrate the effectiveness of the proposed method in experiments using synthetic and real-world data from markets and industrial machinery.

关键词： Reliability Error probability change detection algorithms Big Data detection algorithms Data compression

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Sequential detection of Regime changes in Neural Data 9

Sequential Detection of Regime Changes in Neural Data

引用

9th IEEE/EMBS International Conference on Neural Engineering (NER)

作者： Banerjee, Taposh Allsop, Stephen Tye, Kay M. Ba, Demba Tarokh, Vahid Univ Texas San Antonio ECE San Antonio TX 78249 USA Harvard Med Sch Boston MA 02115 USA MIT Dept Brain & Cognit Sci Cambridge MA 02139 USA Harvard Univ SEAS Cambridge MA 02138 USA Duke Univ ECE Durham NC 27706 USA

ISBN: (纸本)9781538679210

The problem of detecting changes in firing patterns in neural data is studied. The problem is formulated as a quickest change detection (QCD) problem. Important algorithms from the literature are reviewed. A new algorithmic technique is discussed to detect deviations from learned baseline behavior. The algorithms studied can be applied to both spike and local field potential data. The algorithms are applied to mice spike data to verify the presence of behavioral learning.

关键词： change detection algorithms Signal processing algorithms Data models Random variables Hidden Markov models detection algorithms Delays

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BUILDING DAMAGE detection IN POST-EVENT HIGH-RESOLUTION IMAGERY USING DEEP TRANSFER LEARNING

BUILDING DAMAGE DETECTION IN POST-EVENT HIGH-RESOLUTION IMAG...

引用

IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Abdi, Ghasem Esfandiari, Morteza Jabari, Shabnam Univ New Brunswick Dept Geodesy & Geomat Engn Fredericton NB E3B 5A3 Canada

ISBN: (纸本)9781665403696

One of the most important disaster management requirements is accurate damage map generation to support rescue and reconstruction efforts. In this application, remote sensing images play a significant role because of the great details provided by their high spatial, spectral, and temporal resolutions;thus, the literature is rich with studies that use pre- and post-event images along with geospatial machine learning techniques for automatic damage mapping. However, acquiring proper pre-event data can be challenging due to the unpredictable nature of hazards. In this paper, we customize a pre-trained version of the residual neural network with 34 layers (ResNet-34) to identify damaged buildings by using only post-event high-resolution remote sensing images. For evaluating the damage detection framework efficiency, airborne orthophotos of the 2010 Haiti earthquake and the 2018 Woolsey fire are utilized. The network identified damaged and non- damaged buildings with over 91% overall accuracy.

关键词： change detection algorithms hazards machine learning remote sensing urban areas

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Looking High and Low: Learning Place-Dependent Gaussian Mixture Height Models for Terrain Assessment

Looking High and Low: Learning Place-Dependent Gaussian Mixt...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Berczi, Laszlo-Peter Barfoot, Timothy D. Univ Toronto Inst Aerosp Studies Toronto ON Canada

ISBN: (纸本)9781538626825

Assessing terrain ahead of a robot when repeating previously driven safe paths can be accomplished by looking for geometric changes (e.g., due to the appearance of humans or other obstacles). Previous work has shown that the incorporation of data-driven learning and place-dependence are useful aspects of making terrain classification viable in challenging terrain. This paper presents a learning, place-dependent (LPD) terrain classifier that uses a probabilistic model of the terrain to improve detection of small obstacles in uncluttered terrain while avoiding false positives in more challenging environments. Specifically, a Gaussian mixture model is used to account for multi-height terrain cells that arise in heavily vegetated areas (where both a ground plane and overhanging vegetation can occupy the same cell). A variational Bayesian technique is used to automatically determine the number of components required for each cell using a Dirichlet prior on mixing proportions and a Normal-Inverse-Wishart prior on the means and covariances of the components. The probabilistic nature of the model allows for the detection of much smaller obstacles in regions that exhibit low variance in the terrain surface, whilst still avoiding false positives in regions where the terrain is highly cluttered (e.g., vegetation). The algorithm is tested on almost 10 km of autonomous traverse and is shown to be able to classify a wider range of obstacles than two baseline change-detection algorithms based on absolute geometric differences.

关键词： Robots Training Gaussian mixture model change detection algorithms Visualization Probabilistic logic

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