Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems
Springer International Publishing (Verlag)
978-3-030-61579-6 (ISBN)
Introduction.- Multi-modal emotion feature extraction.- Deep sparse autoencoder network for facial emotion recognition.- AdaBoost-knn with direct optimization for dynamic emotion recognition.- Weight-adapted convolution neural network for facial expression recognition.- Two-layer fuzzy multiple random forest for speech emotion recognition.- Two-stage fuzzy fusion based-convolution neural network for dynamic emotion recognition.- Multi-support vector machine based Dempster-Shafer theory for gesture intention understanding.- Three-layer weighted fuzzy support vector regressions for emotional intention understanding.- Dynamic emotion understanding based on two-layer fuzzy fuzzy support vector regression-Takagi-Sugeno model.- Emotion-age-gender-nationality based intention understanding using two-layer fuzzy support vector regression.- Emotional human-robot interaction systems.- Experiments and applications of emotional human-robot.
Erscheinungsdatum | 16.11.2021 |
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Reihe/Serie | Studies in Computational Intelligence |
Zusatzinfo | XI, 247 p. 130 illus., 85 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 409 g |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Technik ► Elektrotechnik / Energietechnik | |
Schlagworte | AI • Emotion Robot Systems • Facial Expression Recognition • gesture recognition • intelligent robots • machine learning • speech emotion recognition |
ISBN-10 | 3-030-61579-0 / 3030615790 |
ISBN-13 | 978-3-030-61579-6 / 9783030615796 |
Zustand | Neuware |
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