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Yapay Zeka Hızlı Bakış & Çıkarımlar
AI Insight⚡ TL;DR(1 Cümlede Hızlı Çıkarım)
We have achieved 81.81% and 89.29% accuracy rate for arousal and valence respectively.
📌 3 Maddede Bu Makale
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Amaç & Hipotez:Emotions play a significant and powerful role in everyday life of human beings.
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Temel Bulgular & Veri:Developing algorithms for computers to recognize emotional expression is widely studied area.
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Sonuç & Katkı:We have achieved 81.81% and 89.29% accuracy rate for arousal and valence respectively.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Biomedical Signal Processing · Emotion Recognition · Pattern Recognition
Abstract
Emotions play a significant and powerful role in everyday life of human beings. Developing algorithms for computers to recognize emotional expression is widely studied area. In this study, emotion recognition from Galvanic Skin Response signals was performed using time domain, wavelet and empirical mode decomposition based features. Valence and arousal have been categorized and relationship between physiological signals and arousal and valence has been studied using k-Nearest Neighbors, Decision Tree, Random Forest and Support Vector Machine algorithms. We have achieved 81.81% and 89.29% accuracy rate for arousal and valence respectively.
Anahtar kelimeler
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Bu Makaleye Atıf Yap
Ayata, D., Yaslan, Y., Kamaşak, M. (2017). Emotion Recognition via Galvanic Skin Response: Comparison of Machine Learning Algorithms and Feature Extraction Methods. Electrica, Cilt: 17 Sayı: 1, 3147–3156. https://ajindex.com/articles/1017406