Search results for "Natural Language"

showing 10 items of 650 documents

Automatic Assessment of Depression Based on Visual Cues: A Systematic Review

2019

International audience; Automatic depression assessment based on visual cues is a rapidly growing research domain. The present exhaustive review of existing approaches as reported in over sixty publications during the last ten years focuses on image processing and machine learning algorithms. Visual manifestations of depression, various procedures used for data collection, and existing datasets are summarized. The review outlines methods and algorithms for visual feature extraction, dimensionality reduction, decision methods for classification and regression approaches, as well as different fusion strategies. A quantitative meta-analysis of reported results, relying on performance metrics r…

MonitoringRating-ScaleRemissionComputer sciencePerformanceFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyAdolescentscomputer.software_genreToolsAttentional Bias[SPI]Engineering Sciences [physics]03 medical and health sciences0302 clinical medicineDynamic-AnalysisMoodDiagnosisDisorder[ SPI ] Engineering Sciences [physics]0202 electrical engineering electronic engineering information engineeringaffective computingAffective computingSensory cueComputingMilieux_MISCELLANEOUSVisualizationFacial expressionData collectionContextual image classificationbusiness.industryDimensionality reductionfacial image analysisReliabilityVisualizationEuropeFacial ExpressionHuman-Computer Interactionmachine learningDepression assessment020201 artificial intelligence & image processingArtificial intelligencebusinesscomputer030217 neurology & neurosurgerySoftwareNatural language processingIEEE Transactions on Affective Computing
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Star-free trace languages

1992

Abstract Generalizing a classical result of Schutzenberger to free partially commutative monoids, we prove that the family of star-free trace languages coincides with the family of aperiodic trace languages.

MonoidPure mathematicsGeneral Computer ScienceAbstract family of languagesComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)Star (graph theory)Cone (formal languages)Theoretical Computer ScienceTrace (semiology)Aperiodic graphFormal languageComputer Science::Programming LanguagesCommutative propertyMathematicsComputer Science(all)Theoretical Computer Science
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"Table 14" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 500 GeV.

Monopole13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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"Table 19" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 3000 GeV.

Monopole13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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"Table 17" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 2000 GeV.

Monopole13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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"Table 10" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 2500 GeV.

Monopole13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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"Table 16" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 1500 GeV.

Monopole13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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"Table 20" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 4000 GeV.

Monopole13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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"Table 15" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 1000 GeV.

Monopole13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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"Table 7" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 1000 GeV.

Monopole13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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