Sparse Emotion Dictionary and CWT Spectrogram Fusion with Multi-head Self-Attention for Depression Recognition in Parkinson's Disease Patients

IF 9.6 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Transactions on Affective Computing Pub Date : 2024-11-14 DOI:10.1109/taffc.2024.3498009
Jian Li, Yuliang Zhao, Yinghao Liu, Huawei Zhang, Peng Shan, Yuanyi Wu, Wanyue Wang, Yulin Wang
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稀疏情绪字典和 CWT 频谱图与多头自我注意力融合,用于帕金森病患者的抑郁识别
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来源期刊
IEEE Transactions on Affective Computing
IEEE Transactions on Affective Computing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
15.00
自引率
6.20%
发文量
174
期刊介绍: The IEEE Transactions on Affective Computing is an international and interdisciplinary journal. Its primary goal is to share research findings on the development of systems capable of recognizing, interpreting, and simulating human emotions and related affective phenomena. The journal publishes original research on the underlying principles and theories that explain how and why affective factors shape human-technology interactions. It also focuses on how techniques for sensing and simulating affect can enhance our understanding of human emotions and processes. Additionally, the journal explores the design, implementation, and evaluation of systems that prioritize the consideration of affect in their usability. We also welcome surveys of existing work that provide new perspectives on the historical and future directions of this field.
期刊最新文献
The ForDigitStress Dataset: A Multi-Modal Dataset for Automatic Stress Recognition Individual-Aware Attention Modulation for Unseen Speaker Emotion Recognition Sparse Emotion Dictionary and CWT Spectrogram Fusion with Multi-head Self-Attention for Depression Recognition in Parkinson's Disease Patients A Low-Rank Matching Attention Based Cross-Modal Feature Fusion Method for Conversational Emotion Recognition EEG-Based Cross-Subject Emotion Recognition Using Sparse Bayesian Learning with Enhanced Covariance Alignment
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