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Improving EEG-Based Emotion Classification Using Conditional Transfer Learning
To overcome the individual differences, an accurate electroencephalogram (EEG)-based emotion-classification system requires a considerable amount of ecological calibration data for each individual, which is labor-intensive and time-consuming. Transfer learning (TL) has drawn increasing attention in...
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| Pubblicato in: | Front Hum Neurosci |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Frontiers Media S.A.
2017
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5486154/ https://ncbi.nlm.nih.gov/pubmed/28701938 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnhum.2017.00334 |
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