专题：Emotion and Mood Recognition

This cluster of papers focuses on the recognition and analysis of emotions from various modalities such as facial expressions, physiological signals, and speech. It explores the use of deep learning, affective computing, and multimodal data for emotion recognition in applications including human-computer interaction.
最新文献
Machine Learning–Based Classification Framework for Human Health Care Monitoring

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Characterizing Delusional Spirals through Human-LLM Chat Logs

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A Review of EEG ‐Based Driver Fatigue Detection: Nonlinear Dynamics, Brain Networks, and Deep Learning Advances

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Entropy-informed deep residual network for nonlinear EEG dynamics in fine-grained driver state recognition

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SenticNet 9: Generative Commonsense for Emotion AI via Conceptual Primitive Discovery and Time Shift Mechanism

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Integrating Multimodal Emotion Recognition with Deep Q-Learning for Adaptive Social Robot Interaction

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Modality-aware fusion with alignment and balancing for robust multimodal emotion recognition

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EUPA: Embodied Uncertainty-Aware Multimodal Affect Perception for Consumer Electronic Systems

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Recent Advances of Multimodal Continual Learning: A Comprehensive Survey

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ACARIS: Attempting to Improve Conversational AI and Human Social Skills using User Embeddings

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近5年高被引文献
Enhancements in Immediate Speech Emotion Detection: Harnessing Prosodic and Spectral Characteristics

article Full Text OpenAlex 1663 FWCI717.999

Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions

review Full Text OpenAlex 739 FWCI21.2093

A systematic review on affective computing: emotion models, databases, and recent advances

review Full Text OpenAlex 581 FWCI19.7258

EEG Based Emotion Recognition: A Tutorial and Review

article Full Text OpenAlex 470 FWCI41.9851

Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations

review Full Text OpenAlex 449 FWCI24.6017

Comparing Recognition Performance and Robustness of Multimodal Deep Learning Models for Multimodal Emotion Recognition

article Full Text OpenAlex 424 FWCI63.9835

Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review

article Full Text OpenAlex 405 FWCI35.1934

TSception: Capturing Temporal Dynamics and Spatial Asymmetry From EEG for Emotion Recognition

article Full Text OpenAlex 391 FWCI30.5627

A physicochemical-sensing electronic skin for stress response monitoring

article Full Text OpenAlex 380 FWCI46.5763

Classifying Emotions and Engagement in Online Learning Based on a Single Facial Expression Recognition Neural Network

article Full Text OpenAlex 334 FWCI50.6536