Search results for " image processing."

showing 10 items of 2265 documents

Measuring Semantic Coherence of a Conversation

2018

Conversational systems have become increasingly popular as a way for humans to interact with computers. To be able to provide intelligent responses, conversational systems must correctly model the structure and semantics of a conversation. We introduce the task of measuring semantic (in)coherence in a conversation with respect to background knowledge, which relies on the identification of semantic relations between concepts introduced during a conversation. We propose and evaluate graph-based and machine learning-based approaches for measuring semantic coherence using knowledge graphs, their vector space embeddings and word embedding models, as sources of background knowledge. We demonstrat…

FOS: Computer and information sciencesWord embeddingComputer scienceComputer Science - Artificial Intelligencemedia_common.quotation_subjectihmisen ja tietokoneen vuorovaikutus02 engineering and technologycomputer.software_genrekeskustelu020204 information systems0202 electrical engineering electronic engineering information engineeringConversationconversational systemsmedia_commonComputer Science - Computation and Languagebusiness.industrykoneoppiminenArtificial Intelligence (cs.AI)Knowledge graphsemantiikkaGraph (abstract data type)020201 artificial intelligence & image processingArtificial intelligencebusinesssemantic coherencecomputerComputation and Language (cs.CL)Natural language processing
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Statistical Performance Analysis of a Fast Super-Resolution Technique Using Noisy Translations.

2014

It is well known that the registration process is a key step for super-resolution reconstruction. In this work, we propose to use a piezoelectric system that is easily adaptable on all microscopes and telescopes for controlling accurately their motion (down to nanometers) and therefore acquiring multiple images of the same scene at different controlled positions. Then a fast super-resolution algorithm \cite{eh01} can be used for efficient super-resolution reconstruction. In this case, the optimal use of $r^2$ images for a resolution enhancement factor $r$ is generally not enough to obtain satisfying results due to the random inaccuracy of the positioning system. Thus we propose to take seve…

FOS: Computer and information sciences[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingPositioning systemComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONsuper-resolution02 engineering and technologyIterative reconstructionMethodology (stat.ME)[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingPosition (vector)[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringComputer visionImage resolutionStatistics - Methodologyerror analysis[STAT.AP]Statistics [stat]/Applications [stat.AP]business.industryreconstruction algorithms[ STAT.AP ] Statistics [stat]/Applications [stat.AP]Process (computing)high-resolution imaging020206 networking & telecommunicationsFunction (mathematics)Computer Graphics and Computer-Aided DesignSuperresolutionperformance evaluation[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]microscopy020201 artificial intelligence & image processingAlgorithm designArtificial intelligencebusinessSoftwareIEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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Characterizing the maximum parameter of the total-variation denoising through the pseudo-inverse of the divergence

2017

International audience; We focus on the maximum regularization parameter for anisotropic total-variation denoising. It corresponds to the minimum value of the regularization parameter above which the solution remains constant. While this value is well know for the Lasso, such a critical value has not been investigated in details for the total-variation. Though, it is of importance when tuning the regularization parameter as it allows fixing an upper-bound on the grid for which the optimal parameter is sought. We establish a closed form expression for the one-dimensional case, as well as an upper-bound for the two-dimensional case, that appears reasonably tight in practice. This problem is d…

FOS: Computer and information sciences[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingStatistics - Machine Learning[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]RegularizationPseudo-inverse[ INFO.INFO-TI ] Computer Science [cs]/Image ProcessingMachine Learning (stat.ML)[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]Total-variation[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]Divergence
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Semantic HMC for Big Data Analysis

2014

International audience; Analyzing Big Data can help corporations to im-prove their efficiency. In this work we present a new vision to derive Value from Big Data using a Semantic Hierarchical Multi-label Classification called Semantic HMC based in a non-supervised Ontology learning process. We also proposea Semantic HMC process, using scalable Machine-Learning techniques and Rule-based reasoning.

FOS: Computer and information sciences[ INFO.INFO-TT ] Computer Science [cs]/Document and Text Processingmulti-classifyComputer scienceComputer Science - Artificial IntelligenceBig data[ INFO.INFO-WB ] Computer Science [cs]/Websemantic technologies02 engineering and technologyOntology (information science)Semantic data model[ INFO.INFO-DC ] Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Semantic similarity020204 information systemsSemantic computing0202 electrical engineering electronic engineering information engineeringontologyInformation retrievalOntology learningbusiness.industryOntology-based data integration[INFO.INFO-WB]Computer Science [cs]/WebBig-Data[INFO.INFO-TT]Computer Science [cs]/Document and Text ProcessingArtificial Intelligence (cs.AI)machine learningOntologySemantic technologyIndex Terms—classification020201 artificial intelligence & image processing[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]business
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Why Does Cultural Diversity Foster Technology-enabled Intergenerational Collaboration?

2019

Globalization and information technology enable people to join the movement of global citizenship and work without borders. However, different type of barriers existed that could affect collaboration in todays work environment, in which different generations are involved. Although researchers have identified several technical barriers to intergenerational collaboration (iGOAL), the influence of cultural diversity on iGOAL has rarely been studied. Therefore, using a quantitative study approach, this paper investigates the impact of differences in cultural background on perceived technical and operational barriers to iGOAL. Our study reveals six barriers to IGC that are perceived differently …

FOS: Computer and information scienceshaasteet (ongelmat)problemsComputer sciencebarriersComputer Science - Human-Computer Interactionchallengessukupolvet02 engineering and technologyAffect (psychology)Human-Computer Interaction (cs.HC)Cultural backgroundGlobalizationComputer Science - Computers and SocietyCultural diversityComputers and Society (cs.CY)0202 electrical engineering electronic engineering information engineeringH.1.2cross-cultural teamworkGeneral Environmental Sciencekulttuurienvälisyysbusiness.industryInformation technology020206 networking & telecommunicationsPublic relationstiimityöWork (electrical)cross-generational collaborationGeneral Earth and Planetary Sciences020201 artificial intelligence & image processingGlobal citizenshipbusiness
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Surrogate outcomes and transportability

2019

Identification of causal effects is one of the most fundamental tasks of causal inference. We consider an identifiability problem where some experimental and observational data are available but neither data alone is sufficient for the identification of the causal effect of interest. Instead of the outcome of interest, surrogate outcomes are measured in the experiments. This problem is a generalization of identifiability using surrogate experiments and we label it as surrogate outcome identifiability. We show that the concept of transportability provides a sufficient criteria for determining surrogate outcome identifiability for a large class of queries.

FOS: Computer and information scienceskokeilucausalityGeneralizationComputer scienceComputer Science - Artificial Intelligence02 engineering and technologyMachine learningcomputer.software_genreOutcome (game theory)Theoretical Computer ScienceMethodology (stat.ME)do-calculusArtificial Intelligence020204 information systemsalgoritmit0202 electrical engineering electronic engineering information engineeringStatistics - Methodologyta113päättelyta112experimentbusiness.industrySurrogate endpointverkkoteoriaApplied MathematicsCausal effectta111graphidentifiabilityIdentification (information)Artificial Intelligence (cs.AI)Causal inferencekausaliteettiIdentifiability020201 artificial intelligence & image processingObservational studyArtificial intelligencebusinessmediatorcomputerSoftware
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Fast PET Scan Tumor Segmentation Using Superpixels, Principal Component Analysis and K-Means Clustering

2018

Positron Emission Tomography scan images are extensively used in radiotherapy planning, clinical diagnosis, assessment of growth and treatment of a tumor. These all rely on fidelity and speed of detection and delineation algorithm. Despite intensive research, segmentation remained a challenging problem due to the diverse image content, resolution, shape, and noise. This paper presents a fast positron emission tomography tumor segmentation method in which superpixels are extracted first from the input image. Principal component analysis is then applied on the superpixels and also on their average. Distance vector of each superpixel from the average is computed in principal components coordin…

FOS: Computer and information sciencespositron emission tomographyprincipal component analysisComputer scienceComputer Vision and Pattern Recognition (cs.CV)k-meansCoordinate systemComputer Science - Computer Vision and Pattern RecognitionFOS: Physical sciences02 engineering and technologyBenchmarkQuantitative Biology - Quantitative MethodsBiochemistry Genetics and Molecular Biology (miscellaneous)030218 nuclear medicine & medical imagingsuperpixels03 medical and health sciences0302 clinical medicineStructural Biology0202 electrical engineering electronic engineering information engineeringmedicineSegmentationComputer visionTissues and Organs (q-bio.TO)Cluster analysisQuantitative Methods (q-bio.QM)Pixelmedicine.diagnostic_testbusiness.industrysegmentationk-means clusteringQuantitative Biology - Tissues and OrgansPattern recognitionPhysics - Medical PhysicsPositron emission tomographyFOS: Biological sciencesPhysics - Data Analysis Statistics and ProbabilityPrincipal component analysis020201 artificial intelligence & image processingMedical Physics (physics.med-ph)Artificial intelligenceNoise (video)businessData Analysis Statistics and Probability (physics.data-an)BiotechnologyMethods and Protocols
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Low-Power Audio Keyword Spotting using Tsetlin Machines

2021

The emergence of Artificial Intelligence (AI) driven Keyword Spotting (KWS) technologies has revolutionized human to machine interaction. Yet, the challenge of end-to-end energy efficiency, memory footprint and system complexity of current Neural Network (NN) powered AI-KWS pipelines has remained ever present. This paper evaluates KWS utilizing a learning automata powered machine learning algorithm called the Tsetlin Machine (TM). Through significant reduction in parameter requirements and choosing logic over arithmetic based processing, the TM offers new opportunities for low-power KWS while maintaining high learning efficacy. In this paper we explore a TM based keyword spotting (KWS) pipe…

FOS: Computer and information sciencesspeech commandSound (cs.SD)Computer scienceSpeech recognition02 engineering and technologykeyword spottingMachine learningcomputer.software_genreComputer Science - SoundReduction (complexity)Audio and Speech Processing (eess.AS)020204 information systemsFOS: Electrical engineering electronic engineering information engineering0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringArtificial neural networkLearning automatabusiness.industrylearning automatalcsh:Applications of electric power020206 networking & telecommunicationslcsh:TK4001-4102Pipeline (software)Power (physics)machine learningTsetlin MachineMFCCKeyword spottingelectrical_electronic_engineeringScalabilityMemory footprintpervasive AI020201 artificial intelligence & image processingMel-frequency cepstrumArtificial intelligencebusinesscomputerartificial neural networkEfficient energy useElectrical Engineering and Systems Science - Audio and Speech Processing
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Estimation des performances, test et contrôle des systèmes cyber-physiques employant des réseaux de communication non idéaux

2020

Wireless technology is a key enabler of the promises of Industry 4.0 (Smart Manufacturing). As such, wireless technology will be adopted as a principal mode of communication within the factory beginning with the factory enterprise and eventually being adopted for use within the factory workcell. Factory workcell communication has particular requirements on latency, reliability, scale, and security that must first be met by the wireless communication technology used. Wireless is considered a non-ideal form of communication in that when compared to its wired counterparts, it is considered less reliable (lossy) and less secure. These possible impairments lead to delay and loss of data in indus…

Fabrication intelligenteIndustrial wireless testbed[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingSmart manufacturingApprentissage automatiqueSystems modelingGraph databaseBase de données graphe[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingMachine learningIndustrial wirelessModelisation systémeCommunications sans fil industrielBanc d'essai sans fil industriel
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Automatable sample fabrication process for pump-probe X-ray holographic imaging

2014

Soft X-ray holography is a recently developed imaging technique with sub-50 nm spatial resolution. Key advantages of this technique are magnetic and elemental sensitivity, compatibility with imaging at free electron laser facilities, and immunity to in-situ sample excitations and sample drift, which enables the reliable detection of relative changes between two images with a precision of a few nanometers. In X-ray holography, the main part of the experimental setup is integrated in the sample, which consequently requires a large number of fabrication steps. Here we present a generic design and an automatable fabrication process for samples suitable, and optimized for, efficient high resolut…

FabricationMaterials scienceImage qualityDynamic imagingHolographyComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHolography02 engineering and technologyIterative reconstruction01 natural scienceslaw.inventionOpticslaw0103 physical sciencesDigital image processing010306 general physicsImage resolutionLithographybusiness.industryEquipment Design021001 nanoscience & nanotechnologyAtomic and Molecular Physics and OpticsEquipment Failure AnalysisComputer-Aided DesignRadiographic Image Interpretation Computer-Assisted0210 nano-technologybusinessOptics Express
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