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n. 老妪,乡下老太婆

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  • From EEG to Eye Movements: Cross-modal Emotion Recognition Using . . .
    Extensive experiments demonstrate that our model achieves the state-of-the-art performance for cross-modal emotion recognition Specifically, the mean accuracy increases around 15% on SEED, 15% on SEED-IV, and 2% on SEED-V compared to the latest baseline for emotion recognition
  • From EEG to Eye Movements: Cross-modal Emotion Recognition Using . . .
    Extensive experiments demonstrate that our model achieves the state-of-the-art performance for cross-modal emotion recognition Specifically, the mean accuracy increases around 15% on SEED, 15% on SEED-IV, and 2% on SEED-V compared to the latest baseline for emotion recognition
  • EEG-eye movement based subject dependence, cross-subject, and cross . . .
    Zhang et al (2022) use knowledge distillation to realize cross-modal knowledge transfer from vision to EEG, and use visual knowledge to improve EEG based continuous emotion recognition Those approaches directly implement multimodal feature fusion through an advanced model architecture, which results in a lack of statistical support for their
  • Publications - Wei-Long Zheng
    From EEG to Eye Movements: Cross-modal Emotion Recognition Using Constrained Adversarial Network with Dual Attention IEEE Transactions on Affective Computing Xuan-Hao Liu, Wei-Bang Jiang, Wei-Long Zheng, Bao-liang Lu (2024) MoGE: Mixture of Graph Experts for Cross-subject Emotion Recognition via Decomposing EEG
  • Yiting Wang
    "From EEG to Eye Movements: Cross-modal Emotion Recognition Using Constrained Adversarial Network with Dual Attention" IEEE Transactions on Affective Computing Zhang, Jian-Ming, Jiawen Liu, Ziyi Li, Tian-Fang Ma, Yiting Wang, Wei-Long Zheng, and Bao-Liang Lu
  • Cross-Modal Guiding Neural Network for Multimodal Emotion Recognition . . .
    This study introduces a cross-modal guiding neural network designed to fully leverage the strengths of both modalities The network includes a dual-branch feature extraction module that simultaneously extracts features from EEG and eye movement signals
  • Cross-Modal Guiding Neural Network for Multimodal Emotion Recognition . . .
    This study introduces a cross-modal guiding neural network designed to fully leverage the strengths of both modalities The network includes a dual-branch feature extraction module that simultaneously extracts features from EEG and eye movement signals
  • Functional Emotion Transformer for EEG-Assisted Cross-Modal Emotion . . .
    To combine high performance of EEG and easy setups of eye tracking, we propose a novel EEG-assisted Contrastive Learning Framework with a Functional Emotion Transformer (ECO-FET) for
  • Emotion recognition using cross-modal attention from EEG and facial . . .
    This article introduced a new multimodal network for recognizing emotions using facial expressions and EEG signals, employing a cross-modal attention fusion mechanism In the facial expression domain, we used SA-ConvLSTM to extract spatiotemporal features of facial expression image sequences, and accelerated the training efficiency of the model
  • From EEG to Eye Movements: Cross-modal Emotion Recognition Using . . .
    From EEG to Eye Movements: Cross-modal Emotion Recognition Using Constrained Adversarial Network with Dual Attention Yiting Wang , Jia-Wen Liu , Bao-Liang Lu , Wei-Long Zheng December 2024





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