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• W3170706693 abstract "Emotion and affect recognition in the uncontrolled everyday-life environment remains challenging. One of its vital problems is collecting numerous annotated emotional samples indispensable for learning the reasoning model. We propose a novel method supporting rich emotional data collection - a pre-trained binary model recognizing physiologically arousing events in real-time and triggering self-assessments at a convenient point in time. An experimental study on 6.000 hours of recorded physiological signals has been performed. The results suggest that we are able to detect emotional events in real-life scenarios to enhance data collection for emotion recognition in the field." @default.
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• W3170706693 date "2021-03-22" @default.
• W3170706693 modified "2023-10-01" @default.
• W3170706693 title "How to catch them all? Enhanced data collection for emotion recognition in the field" @default.
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• W3170706693 doi "https://doi.org/10.1109/percomworkshops51409.2021.9431143" @default.
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