Search results for "Intelligence"

showing 10 items of 6959 documents

Approximated overlap error for the evaluation of feature descriptors on 3D scenes

2013

This paper presents a new framework to evaluate feature descriptors on 3D datasets. The proposed method employs the approximated overlap error in order to conform with the reference planar evaluation case of the Oxford dataset based on the overlap error. The method takes into account not only the keypoint centre but also the feature shape and it does not require complex data setups, depth maps or an accurate camera calibration. Only a ground-truth fundamental matrix should be computed, so that the dataset can be freely extended by adding further images. The proposed approach is robust to false positives occurring in the evaluation process, which do not introduce any relevant changes in the …

Complex data typeSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticabusiness.industryComputer scienceGLOHEpipolar geometryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-invariant feature transformPattern recognitionLIOPMROGHkeypoint descriptorSIFTepipolar geometryFalse positive paradoxComputer visionArtificial intelligencebusinessFundamental matrix (computer vision)descriptor evaluationCamera resectioning
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On the Online Classification of Data Streams Using Weak Estimators

2016

In this paper, we propose a novel online classifier for complex data streams which are generated from non-stationary stochastic properties. Instead of using a single training model and counters to keep important data statistics, the introduced online classifier scheme provides a real-time self-adjusting learning model. The learning model utilizes the multiplication-based update algorithm of the Stochastic Learning Weak Estimator (SLWE) at each time instant as a new labeled instance arrives. In this way, the data statistics are updated every time a new element is inserted, without requiring that we have to rebuild its model when changes occur in the data distributions. Finally, and most impo…

Complex data typeTraining setLearning automataComputer sciencebusiness.industryData stream miningEstimator020206 networking & telecommunications02 engineering and technologycomputer.software_genreMachine learning0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingData miningArtificial intelligencebusinesscomputerClassifier (UML)Juncture
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On the inductive inference of recursive real-valued functions

1999

AbstractWe combine traditional studies of inductive inference and classical continuous mathematics to produce a study of learning real-valued functions. We consider two possible ways to model the learning by example of functions with domain and range the real numbers. The first approach considers functions as represented by computable analytic functions. The second considers arbitrary computable functions of recursive real numbers. In each case we find natural examples of learnable classes of functions and unlearnable classes of functions.

Complex-valued functionGeneral Computer ScienceReal analysisLearning theoryComputable numberInductive inference0102 computer and information sciences02 engineering and technology01 natural sciencesμ-recursive functionComputable analysisTheoretical Computer ScienceAlgebraμ operatorComputable functionReal-valued computationReal-valued function010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingAlgorithmComputer Science(all)MathematicsTheoretical Computer Science
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Counting by Statistics on Search Trees: Application to Constraint Satisfaction Problems

1997

In 1975, Knuth proposed a simple statistical method for investigating search trees. We use this technique for estimating the number of solutions of constraint satisfaction problem CSP and boolean satisfiability problem SAT instances. We show that, depending on domain reductions, tree-based estimates have a lower variance than estimates based on uniform sampling from the search space. Nevertheless, because the variance remains extremely high in the general case, a confidence interval cannot be derived, but a lower bound of the number of solutions. These results are confirmed by many experiments.

Complexity of constraint satisfactionBacktrackingConstraint graphArtificial IntelligenceStatisticsConstraint satisfaction dual problemHybrid algorithm (constraint satisfaction)Local consistencyComputer Vision and Pattern RecognitionConstraint satisfactionConstraint satisfaction problemMathematicsTheoretical Computer ScienceIntelligent Data Analysis
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Day-ahead forecasting for photovoltaic power using artificial neural networks ensembles

2016

Solar photovoltaic plants power output forecasting using machine learning techniques can be of a great advantage to energy producers when they are implemented with day-ahead energy market data. In this work a model was developed using a supervised learning algorithm of multilayer perceptron feedforward artificial neural network to predict the next twenty-four hours (day-ahead) power of a solar facility using fetched weather forecast of the following day. Each set of tested network configuration was trained by the historical power output of the plant as a target. For each configuration, one hundred networks ensembles was averaged to give the ability to generalize a better forecast. The train…

ComponentComputer science020209 energyEnergy Engineering and Power Technologyforecasting02 engineering and technologyMachine learningcomputer.software_genrephotovoltaicSet (abstract data type)0202 electrical engineering electronic engineering information engineeringEnergy marketRenewable EnergyStyleStylingSustainability and the EnvironmentArtificial neural networkbusiness.industryFormattingPhotovoltaic systemFeed forwardComponent; Formatting; Insert (key words); Style; Styling; Energy Engineering and Power Technology; Renewable Energy Sustainability and the EnvironmentInsert (key words)Power (physics)Settore ING-IND/31 - ElettrotecnicaMultilayer perceptronArtificial intelligencebusinessartificial neural networkscomputerEnergy (signal processing)2016 IEEE International Conference on Renewable Energy Research and Applications (ICRERA)
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Comment on: A critical analysis of the internal logic in the Life-Space Assessment (LSA) composite score and suggested solutions

2016

Background:An individual’s ability to live independently is commonly measured in health research interested in identifying risk factors associated with disablement processes. In order to inform clinical practice, population research has attempted to identify the contraction of “lived-space” by using various survey instruments.Problem:Studies assessing habitual movements over the environment with the Life-Space Assessment (LSA) survey instrument should carefully consider how the LSA Composite Score (LSA-CS) is computed. Until now, no publication has carefully delineated the assumptions guiding the internal logic used in the computation of the LSA-CS.Core argument:Because the internal logic o…

Composite scoreLogicPopulation researchLife-Space AssessmentPhysical Therapy Sports Therapy and Rehabilitationcomputer.software_genre03 medical and health sciences0302 clinical medicineScoring algorithmActivities of Daily LivingHumans030212 general & internal medicineMobility LimitationInternal logicbusiness.industryRehabilitationGeriatric assessmentta3141ta3142Clinical PracticeLife spaceArtificial intelligenceSurvey instrumentbusinessPsychologycomputerSocial psychology030217 neurology & neurosurgeryNatural language processingClinical Rehabilitation
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Search and Comprehension Processes in Learning from Text

2008

We analyzed the relationships between comprehension skill and search strategies in instructional text. In two experiments, college-level readers were asked to search a computer-presented science text in order to answer different types of questions. High level questions required the integration of information across paragraphs, whereas low level questions requested the localization of information within a single paragraph. High level questions were re-read more often and they resulted in broader text search patterns. Furthermore, students who were diagnosed as good comprehenders located relevant sections of the text faster and spent more time on those sections. Poor comprehenders, on the oth…

ComprehensionComputer scienceOrder (business)business.industryFull text searchArtificial intelligenceParagraphbusinesscomputer.software_genrecomputerNatural language processing
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Manipulatable Models for Investigating Processing of Dynamic Diagrams

2010

Existing approaches for collecting process data on human diagram comprehension have limited effectiveness. Analogue models that allow participants to manipulate diagram components offer powerful ways to capture the non-verbal and dynamic aspects of processing that are not available with some other approaches. Examples drawn from a variety of different domains illustrate the utility of model manipulation for revealing otherwise inaccessible aspects of how people process animated diagrams of complex content.

ComprehensionComputer scienceProcess (engineering)Human–computer interactionbusiness.industryDiagramArtificial intelligencebusinessVariety (cybernetics)
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Linear-size suffix tries

2016

Suffix trees are highly regarded data structures for text indexing and string algorithms [MCreight 76, Weiner 73]. For any given string w of length n = | w | , a suffix tree for w takes O ( n ) nodes and links. It is often presented as a compacted version of a suffix trie for w, where the latter is the trie (or digital search tree) built on the suffixes of w. Here the compaction process replaces each maximal chain of unary nodes with a single arc. For this, the suffix tree requires that the labels of its arcs are substrings encoded as pointers to w (or equivalent information). On the contrary, the arcs of the suffix trie are labeled by single symbols but there can be Θ ( n 2 ) nodes and lin…

Compressed suffix arrayGeneral Computer ScienceSuffix tree[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Generalized suffix tree0102 computer and information sciences02 engineering and technologyData_CODINGANDINFORMATIONTHEORYText indexing01 natural sciencesY-fast trielaw.inventionLongest common substring problemTheoretical Computer ScienceCombinatoricsSuffix treelawFactor and suffix automata0202 electrical engineering electronic engineering information engineeringData_FILESArithmeticFactor and suffix automata; Pattern matching; Suffix tree; Text indexing; Theoretical Computer Science; Computer Science (all)Pattern matchingMathematicsSettore INF/01 - InformaticaX-fast trieComputer Science (all)LCP array010201 computation theory & mathematics020201 artificial intelligence & image processingFM-index
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Local operators to detect regions of interest

1997

The performance of a visual system is strongly influenced by the information processing that is done in the early vision phase. The need exists to limit the computation on areas of interest to reduce the total amount of data and their redundancy. This paper describes a new method to drive the attention during the analysis of complex scenes. Two new local operators, based on the computation of local moments and symmetries, are combined to drive the selection. Experimental results on real data are also reported. © 1997 Elsevier Science B.V.

ComputationEarly visioncomputer.software_genreMachine learningFacial recognition systemSegmentationArtificial IntelligenceRedundancy (engineering)Selection (linguistics)AttentionSegmentationLimit (mathematics)Face recognitionElectrical and Electronic Engineering1707MathematicsSettore INF/01 - Informaticabusiness.industryInformation processingSignal ProcessingSymmetry operatorComputer Vision and Pattern RecognitionArtificial intelligenceData miningbusinesscomputerSoftwarePattern Recognition Letters
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