Search results for "Process"

showing 10 items of 22310 documents

FastEMD–CCA algorithm for unsupervised and fast removal of eyeblink artifacts from electroencephalogram

2020

Abstract Online detection and removal of eye blink (EB) artifacts from electroencephalogram (EEG) would be very useful in medical diagnosis and brain computer interface (BCI). In this work, approaches that combine unsupervised eyeblink artifact detection with empirical mode decomposition (EMD), and canonical correlation analysis (CCA), are proposed to automatically identify eyeblink artifacts and remove them in an online manner. First eyeblink artifact regions are automatically identified and an eyeblink artifact template is extracted via EMD, which incorporates an alternate interpolation technique, the Akima spline interpolation. The removal of eyeblink artifact components relies on the el…

Artifact (error)Cross-correlationmedicine.diagnostic_testComputer science0206 medical engineeringBiomedical EngineeringWord error rateHealth Informatics02 engineering and technologyElectroencephalography020601 biomedical engineeringHilbert–Huang transform[SPI]Engineering Sciences [physics]03 medical and health sciences0302 clinical medicineSignal ProcessingmedicineSpline interpolationAlgorithm030217 neurology & neurosurgeryInterpolationBrain–computer interfaceBiomedical Signal Processing and Control
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Refitting Solutions Promoted by $$\ell _{12}$$ Sparse Analysis Regularizations with Block Penalties

2019

International audience; In inverse problems, the use of an l(12) analysis regularizer induces a bias in the estimated solution. We propose a general refitting framework for removing this artifact while keeping information of interest contained in the biased solution. This is done through the use of refitting block penalties that only act on the co-support of the estimation. Based on an analysis of related works in the literature, we propose a new penalty that is well suited for refitting purposes. We also present an efficient algorithmic method to obtain the refitted solution along with the original (biased) solution for any convex refitting block penalty. Experiments illustrate the good be…

Artifact (error)Total variationComputer scienceRegular polygon02 engineering and technologyInverse problem01 natural sciences[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]010104 statistics & probabilityRefitting0202 electrical engineering electronic engineering information engineeringBias correction020201 artificial intelligence & image processingBias correction0101 mathematics[MATH]Mathematics [math]AlgorithmBlock (data storage)Scale Space and Variational Methods in Computer Vision - 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 – July 4, 2019, Proceedings
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Online detection and removal of eye blink artifacts from electroencephalogram

2021

Abstract The most prominent type of artifact contaminating electroencephalogram (EEG) signals are the eye blink (EB) artifacts, which could potentially lead to misinterpretation of the EEG signal. Online identification and elimination of eye blink artifacts are crucial in applications such a Brain-Computer Interfaces (BCI), neurofeedback, and epilepsy diagnosis. In this paper, algorithms that combine unsupervised eye blink artifact detection (eADA) with modified Empirical Mode Decomposition (FastEMD) and Canonical Correlation Analysis (CCA) are proposed, i.e., FastEMD-CCA2 and FastCCA, to automatically identify eye blink artifacts and remove them in an online setting. The average accuracy, …

Artifact (error)medicine.diagnostic_testComputer sciencebusiness.industryBiomedical EngineeringWord error rateHealth InformaticsPattern recognitionElectroencephalographySignalHilbert–Huang transformSignal ProcessingmedicineArtificial intelligenceSensitivity (control systems)NeurofeedbackbusinessBrain–computer interfaceBiomedical Signal Processing and Control
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Automated and Online Eye Blink Artifact Removal from Electroencephalogram

2019

Eyeblink artifacts often contaminates electroencephalogram (EEG) signals, which could potentially confound EEG's interpretation. A lot offline methods are available to remove this artifact, but an online solution is required to remove eyeblink artifacts in near real time for EEG signal to be beneficial in applications such as brain computer interface, (BCI). In this work, approaches that combines unsupervised eyeblink artifact detection with Empirical Mode Decomposition (EMD) and Canonical Correlation Analysis (CCA) are proposed to automatically identify eyeblink artifacts and remove them in an online setting. The proposed approaches are analysed and evaluated in terms of artifact removal a…

Artifact (error)medicine.diagnostic_testComputer sciencebusiness.industryProcess (computing)Pattern recognition02 engineering and technologyElectroencephalography021001 nanoscience & nanotechnologySignalHilbert–Huang transform03 medical and health sciencesComputingMethodologies_PATTERNRECOGNITION0302 clinical medicinemedicineArtificial intelligence0210 nano-technologyCanonical correlationEye blinkbusiness030217 neurology & neurosurgeryBrain–computer interface2019 IEEE International Conference on Signal and Image Processing Applications (ICSIPA)
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Unsupervised Eye Blink Artifact Identification in Electroencephalogram

2018

International audience; The most prominent type of artifact contaminating electroencephalogram (EEG) signals is the eye blink (EB) artifact. Hence, EB artifact detection is one of the most crucial pre-processing step in EEG signal processing before this artifact can be removed. In this work, an approach that identifies EB artifacts without human supervision and automated varying threshold setting is proposed and evaluated. The algorithm functions on the basis of correlation between two EEG electrodes, Fp1 and Fp2, followed by EB artifact threshold determination utilizing the amplitude displacement from the mean. The proposed approach is validated and evaluated in terms of accuracy and error…

Artifact (error)medicine.diagnostic_testbusiness.industryComputer science05 social sciencesFeature extractionWord error ratePattern recognitionElectroencephalography050105 experimental psychologyEB Artifacts03 medical and health sciencesIdentification (information)Electroencephalogram0302 clinical medicine[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingmedicine0501 psychology and cognitive sciences[INFO]Computer Science [cs]Artificial intelligenceAutomated ThresholdbusinessEye blink030217 neurology & neurosurgery
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An offline/real-time artifact rejection strategy to improve the classification of multi-channel evoked potentials

2008

The primary goal of this paper is to improve the classification of multi-channel evoked potentials (EPs) by introducing a temporal domain artifact detection strategy and using this strategy to (a) evaluate how the performance of classifiers is affected by artifacts and (b) show how the performance can be improved by detecting and rejecting artifacts in offline and real-time classification experiments. Using a pattern recognition approach, an artifact is defined in this study as any signal that may lead to inaccurate classifier parameter estimation and inaccurate testing. The temporal domain artifact detection tests include: a within-channel standard deviation (STD) test that can detect sign…

Artifact rejectionArtificial IntelligenceEstimation theoryComputer scienceSpeech recognitionSignal ProcessingInformation processingDetection theoryComputer Vision and Pattern RecognitionEvoked potentialClassifier (UML)SoftwareStandard deviationPattern Recognition
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Knowledge Acquisition in Conceptual Ontological Artificial Intelligence System

2009

The paper deals with active knowledge acquisition based on dialogue between AI system and its user. Presented method uses Conceptual Ontological Object Orientated System (COOS) to distinguish differences between concepts and to unequivocally process the input stream. In case of concepts, that do not exist in the system yet, adequate algorithms are being used to position them in ontological core. Separate concepts differ in attributes values or in sets of direct connections with other concepts. The communication aspect of the system deliver information that allow generating proper interpretation for userpsilas statement.

Artificial Intelligence SystemNatural language user interfacebusiness.industryComputer scienceInterpretation (philosophy)computer.software_genreKnowledge acquisitionSemantic networkKnowledge baseHuman–computer interactionOntologyArtificial intelligencebusinesscomputerNatural languageNatural language processing
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Special Issue of Journal of Manufacturing Processes on Advancing Manufacturing Processes Research at NAMRC 46

2018

During the refereeing process of papers submitted to NAMRC 46 this year, nine high-quality papers have been selected and fast-tracked to a special issue of Journal of Manufacturing Processes (JMP) entitled “Advancing Manufacturing Processes Research at NAMRC 46”. The selection of the fast-track papers was based on authors’ preferences, quality of the papers, reviewers’ recommendations, Track Chairs’ picks, pre-selection by the Chair of NAMRI/SME Scientific Committee, and final approval by the JMP Editor. The nine papers published in JMP are therefore excluded from the Proceedings of NAMRC 46 in Procedia Manufacturing. Nevertheless, these papers are presented in person at NAMRC 46. Details o…

Artificial IntelligenceComputerApplications_COMPUTERSINOTHERSYSTEMSGeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)Manufacturing processesIndustrial and Manufacturing Engineering
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Special Issue of Journal of Manufacturing Processes on New Trends in Manufacturing Processes Research

2019

Special issue of journal of manufacturing processes on new trends in manufacturing processes research

Artificial IntelligenceNew Trends in Manufacturing Processes ResearchComputerApplications_COMPUTERSINOTHERSYSTEMSSettore ING-IND/16 - Tecnologie E Sistemi Di LavorazioneGeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)Industrial and Manufacturing EngineeringProcedia Manufacturing
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Complexity reduction in efficient prototype-based classification

2006

Artificial Intelligencebusiness.industryComputer scienceSignal ProcessingComputer Vision and Pattern RecognitionArtificial intelligencebusinessMachine learningcomputer.software_genrecomputerSoftwarePattern Recognition
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