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Detection and classification of subject-generated artifacts in EEG signals using autoregressive models
We examine the problem of accurate detection and classification of artifacts in continuous EEG recordings. Manual identification of artifacts, by means of an expert or panel of experts, can beExpand
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  • Open Access
Hierarchical Event Descriptor (HED) tags for analysis of event-related EEG studies
Data from well-designed EEG experiments should find uses beyond initial reports, even when study authors cannot anticipate how it may contribute to future analyses. Several ontologies have beenExpand
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  • Open Access
DETECT: A MATLAB Toolbox for Event Detection and Identification in Time Series, with Applications to Artifact Detection in EEG Signals
Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which areExpand
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  • Open Access
A Deep Learning method for classification of images RSVP events with EEG data
In this paper, we investigated Deep Learning (DL) for characterizing and detecting target images in an image rapid serial visual presentation (RSVP) task based on EEG data. We exploited DL techniqueExpand
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Characterization and Robust Classification of EEG Signal from Image RSVP Events with Independent Time-Frequency Features
This paper considers the problem of automatic characterization and detection of target images in a rapid serial visual presentation (RSVP) task based on EEG data. A novel method that aims to identifyExpand
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  • Open Access
FIFTHTM: A Stack Based GP Language for Vector Processing
FIFTH™, a new stack-based genetic programming language, efficiently expresses solutions to a large class of feature recognition problems. This problem class includes mining time-series data,Expand
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  • Open Access
Tracking thymocyte migration in situ.
The dynamic process of thymocyte migration can now be visualized in real-time and in the context of the native thymic environment. With improved computational resources, key information can beExpand
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CTAGGER: Semi-structured community tagging for annotation and data-mining in event-rich contexts
Analysis of dynamic brain imaging data from EEG, MEG or fMRI requires a common temporal context to enable meta-analysis and data mining across experiments. However, there is no standardized method ofExpand
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A bag-of-words model for task-load prediction from EEG in complex environments
Neurotechnologies based on electroencephalography (EEG) and other physiological measures to improve task performance in complex environments will require tools and analysis methods that can accountExpand
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Classification of non-time-locked rapid serial visual presentation events for brain-computer interaction using deep learning
Deep learning solutions based on deep neural networks (DNN) and deep stack networks (DSN) were investigated for classifying target images in a non-time-locked rapid serial visual presentation (RSVP)Expand
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