Search results for "Methodologie"

showing 10 items of 2141 documents

Morse Description and Geometric Encoding of Digital Elevation Maps

2004

Two complementary geometric structures for the topographic representation of an image are developed in this work. The first one computes a description of the Morse-topological structure of the image, while the second one computes a simplified version of its drainage structure. The topographic significance of the Morse and drainage structures of digital elevation maps (DEMs) suggests that they can been used as the basis of an efficient encoding scheme. As an application, we combine this geometric representation with an interpolation algorithm and lossless data compression schemes to develop a compression scheme for DEMs. This algorithm achieves high compression while controlling the maximum …

ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingData_CODINGANDINFORMATIONTHEORYSensitivity and SpecificityPattern Recognition AutomatedPhysics::GeophysicsImaging Three-DimensionalCompression (functional analysis)Image Interpretation Computer-AssistedComputer SimulationComputer visionMorse theoryMathematicsLossless compressionbusiness.industryReproducibility of ResultsNumerical Analysis Computer-AssistedSignal Processing Computer-AssistedData CompressionImage EnhancementTopographic mapComputer Graphics and Computer-Aided DesignArtificial intelligencebusinessAlgorithmAlgorithmsSoftwareData compressionImage compressionInterpolationIEEE Transactions on Image Processing
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HDR-ARtiSt: A 1280x1024-pixel Adaptive Real-time Smart camera for High Dynamic Range video

2014

International audience; Standard cameras capture only a fraction of the information that is visible to the human visual system. This is specifically true for natural scenes including areas of low and high illumination due to transitions between sunlit and shaded areas. When capturing such a scene, many cameras are unable to store the full Dynamic Range (DR) resulting in low quality video where details are concealed in shadows or washed out by sunlight.The imaging technique that can overcome this problem is called HDR (High Dynamic Range) imaging. This paper describes a complete smart camera built around a standard off-the-shelf LDR (Low Dynamic Range) sensor and a Virtex 6 FPGA board. This …

ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingComputingMethodologies_COMPUTERGRAPHICS
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Estimating head pose and state of facial elements for sign language video

2014

In this work we present methods for automatic estimation of non-manual gestures in sign language videos. More specifically, we study the estimation of three head pose angles (yaw, pitch, roll) and the state of facial elements (eyebrow position, eye openness, and mouth state). This kind of estimation facilitates automatic annotation of sign language videos and promotes more prolific production of annotated sign language corpora. The proposed estimation methods are incorporated in our publicly available SLMotion software package for sign language video processing and analysis. Our method implements a model-based approach: for head pose we employ facial landmarks and skins masks as features, a…

ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONfacial state recognitionhead pose estimationsign language analysis
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Environmental Problem-solving and Hands-on Geometry Learning through Storytelling inside a Geodesic Dome : Ice, Honey and Stardust

2019

In this workshop, we introduce a STEAM learning activity based on the construction of geodesic domes. This workshop will engage participants in various preliminary and exploratory constructions, while also applying the geometry of geodesic domes to approximate hemispheres. Various storytelling, role-playing, and environmental connections that can provide needed context for learners of all ages are explored. peerReviewed

ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONkupolitroolileikitkokemusoppiminengeometriset kuviotongelmanratkaisuComputingMethodologies_COMPUTERGRAPHICS
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Enterprise Architecture Benefits: Perceptions from Literature and Practice

2008

First published in the Proceedings of the 7th IBIMA Conference Internet & Information Systems in the Digital Age, 14-16 December, 2006, Brescia, Italy Enterprise Architecture (EA) is considered a means for acquiring a multitude of benefits in organizations by most academic literature and practitioners alike. However, academic research has almost omitted the domain of EA benefits and value realization, and thus more research on the subject is needed. This paper describes a study which aims to chart the benefits of EA by a comprehensive literature review and a focus group interview of practitioners. As a result, a categorization of the EA benefits is composed and analyzed.

ComputingMethodologies_MISCELLANEOUSenterprise architecture
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A Goal-Oriented Way to Define Metrics for an Enterprise Architecture Program

2008

First published in the Journal of Enterprise Architecture, Vol. 4, No. 1, 2008, pp. 20-26. Republished with the kind permission of the Journal of Enterprise Architecture Metrics are becoming more and more important in the development of enterprise architecture (EA) programs. Therefore, guidelines and support to define metrics for EA programs are needed. A goal-oriented approach for defining metrics for EA program and the measurement aspects for EA program are presented in this article. This approach was developed and tested during the development of proposals of EA program metrics for two companies. peerReviewed

ComputingMethodologies_MISCELLANEOUSenterprise architecturemeasurementQGM
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Text Classification Using “Anti”-Bayesian Quantile Statistics-Based Classifiers

2016

The problem of Text Classification (TC) has been studied for decades, and this problem is particularly interesting because the features are derived from syntactic or semantic indicators, while the classification, in and of itself, is based on statistical Pattern Recognition (PR) strategies. Thus, all the recorded TC schemes work using the fundamental paradigm that once the statistical features are inferred from the syntactic/semantic indicators, the classifiers themselves are the well-established ones such as the Bayesian, the Na¨ıve Bayesian, the SVM etc. and those that are neural or fuzzy. In this paper, we shall demonstrate that by virtue of the skewed distributions of the features, one …

ComputingMethodologies_PATTERNRECOGNITION
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Spam classification for online discussions

2010

Masteroppgave i informasjons- og kommunikasjonsteknologi 2010 – Universitetet i Agder, Grimstad Traditionally, spam messages filtering systems are built by integrating content-based analysis technologies which are developed from the experiences of dealing with E-mail spam. Recently, the new style of information appears in the Internet, Social Media platform, which also expands the space for Internet abusers. In this thesis, we not only evaluated the traditional content-based approaches to classify spam messages, we also investigated the possibility of integrating context-based technology with con-tent-based approaches to classify spam messages. We built spam classifiers using Novelty de-tec…

ComputingMethodologies_PATTERNRECOGNITION
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Metadata record for: Comprehensive dataset of shotgun metagenomes from oxygen stratified freshwater lakes and ponds

2021

This dataset contains key characteristics about the data described in the Data Descriptor Comprehensive dataset of shotgun metagenomes from oxygen stratified freshwater lakes and ponds. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format

ComputingMethodologies_PATTERNRECOGNITION
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Study on Support Vector Machine-Based Fault Detection in Tennessee Eastman Process

2014

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/836895 Open Access This paper investigates the proficiency of support vector machine (SVM) using datasets generated by Tennessee Eastman process simulation for fault detection. Due to its excellent performance in generalization, the classification performance of SVM is satisfactory. SVM algorithm combined with kernel function has the nonlinear attribute and can better handle the case where samples and attributes are massive. In addition, with forehand optimizing the parameters using the cross-validation technique, SVM can produce high accuracy i…

ComputingMethodologies_PATTERNRECOGNITIONArticle SubjectApplied Mathematicslcsh:MathematicsAnalysis; Applied Mathematicslcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411AnalysisAbstract and Applied Analysis
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