Emotional Intelligence
Springer Nature Switzerland AG (Verlag)
978-981-96-5083-5 (ISBN)
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The 14 full papers and 2 short papers presented in this volume were carefully reviewed and selected from 41 submissions.
This book constitutes the proceedings of the Second CSIG Conference on Emotional Intelligence, CEI 2024, held in Nanjing, China during December 6-8, 2024.
The 14 full papers and 2 short papers presented in this volume were carefully reviewed and selected from 41 submissions. These papers have been categorized under the following topical sections: Emotional Intelligence Surveys and Databases; Emotional Intelligence Methods; Emotional Intelligence Applications.
.- Emotional Intelligence Surveys and Databases.
.- Affective Computing for Healthcare: Recent Trends, Applications, Challenges, and Beyond.
.- REFN: A Multimodal Database for Emotion Analysis Using Functional Near-infrared Spectroscopy.
.- Emotional Intelligence Methods.
.- EIDA: Explicit- and Implicit-space Self-supervised Learning for Visual Emotion Adaptation.
.- A Three streams Convolutional Transformer Fusion Model for Facial Macro- and Micro-Expressions Spotting.
.- Facial Action Unit Recognition with Micro-Action-Aware Transformer.
.- Local and Global Iterative Adaptation Based on Meta learning for Source-free Cross-Corpus Speech Emotion Recognition.
.- Decoupled Representation with Multimodal Prompts for Emotion Recognition in Conversation.
.- Emotional Intelligence Applications.
.- Generative Text Prompts for Image Aesthetic Quality Assessment.
.- Large Language Model Enhanced Fuzzy Logic Fusion Framework for Stance Detection.
.- Skeleton-based Online Action Detection with Temporal Enhancement.
.- Fine-Grained Spatial-Temporal Framework for Engagement Prediction.
.- Multimodal Engagement Recognition by fusing Transformer and Bi-LSTM.
.- Emotional Interaction Hardware Design for Wrist Rehabilitation Based on Secondary Fuzzy Reasoning.
.- Attention-Based Audio Depression Recognition Integrating Handcrafted and Deep Features.
.- STC-ND: Leveraging Spatialtemporal Characteristics with NeXtVLAD for Depression Detection from Few-Channel EEG Signals.
.- DepLLM: Fine-Tuning Large Language Models with a Chinese Dialogue Dataset for Depression Diagnosis via Mixture of Specialized Experts.
| Erscheinungsdatum | 03.06.2025 |
|---|---|
| Reihe/Serie | Communications in Computer and Information Science |
| Zusatzinfo | 57 Illustrations, color; 4 Illustrations, black and white |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Schlagworte | Affective computing • Computer Science proceedings • Cross-modal fusion • Deep learning • Depression recognition • Emotion evaluation • facial action unit recognition • Fuzzy Graph Convolutional Network • Healthcare • Micro-expression spotting • Multimodal Dataset • multimodal interactions • multi-modal learning • non-verbal interactions • Online action detection • Psychological and Behavioral Analysis • representation learning • speech emotion recognition • Unsupervised Domain Adaptation |
| ISBN-10 | 981-96-5083-6 / 9819650836 |
| ISBN-13 | 978-981-96-5083-5 / 9789819650835 |
| Zustand | Neuware |
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