Search results for "Self-organizing feature maps"

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Class discovery from semi-structured EEG data for affective computing and personalisation

2017

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Many approaches to recognising emotions from metrical data such as EEG signals rely on identifying a very small number of classes and to train a classifier. The interpretation of these classes varies from a single emotion such as stress [24] to features of emotional model such as valence-arousal [4]. There are two major issues here. First classification approach limits the analysis of the data within the selected classes and is also highly dependent on training data/cycles, all of which limits generalisation. Second issue is that it does not exp…

Brain modelingComputer scienceFeature extraction02 engineering and technologyElectroencephalographyMachine learningcomputer.software_genrePersonalizationCorrelationDEAP03 medical and health sciences0302 clinical medicine0202 electrical engineering electronic engineering information engineeringmedicineCluster analysisAffective computingmedicine.diagnostic_testbusiness.industryElectroencephalographySelf-organizing feature mapsFeature extraction020201 artificial intelligence & image processingArtificial intelligenceEmotion recognitionbusinessClassifier (UML)computer030217 neurology & neurosurgery
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