Search Results - "Shen, Fangyao"

Multi-Scale Frequency Bands Ensemble Learning for EEG-Based Emotion Recognition by Shen, Fangyao, Peng, Yong, Kong, Wanzeng, Dai, Guojun

“…Emotion recognition has a wide range of potential applications in the real world. Among the emotion recognition data sources, electroencephalography (EEG)…”
Get full text

Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition by Zhang, Hua, Gou, Ruoyun, Shang, Jili, Shen, Fangyao, Wu, Yifan, Dai, Guojun

“…Speech emotion recognition (SER) is a difficult and challenging task because of the affective variances between different speakers. The performances of SER are…”
Get full text

Coupled Projection Transfer Metric Learning for Cross-Session Emotion Recognition from EEG by Shen, Fangyao, Peng, Yong, Dai, Guojun, Lu, Baoliang, Kong, Wanzeng

“…Distribution discrepancies between different sessions greatly degenerate the performance of video-evoked electroencephalogram (EEG) emotion recognition. There…”
Get full text

MLA-LSTM: A Local and Global Location Attention LSTM Learning Model for Scoring Figure Skating by Han, Chaoyu, Shen, Fangyao, Chen, Lina, Lian, Xiaoyi, Gou, Hongjie, Gao, Hong

“…Video-based scoring using neural networks is a very important means for evaluating many sports, especially figure skating. Although many methods for evaluating…”
Get full text

EEG-based emotion recognition using 4D convolutional recurrent neural network by Shen, Fangyao, Dai, Guojun, Lin, Guang, Zhang, Jianhai, Kong, Wanzeng, Zeng, Hong

“…In this paper, we present a novel method, called four-dimensional convolutional recurrent neural network, which integrating frequency, spatial and temporal…”
Get full text

Joint domain symmetry and predictive balance for cross-dataset EEG emotion recognition by Jiang, Haiting, Shen, Fangyao, Chen, Lina, Peng, Yong, Guo, Hongjie, Gao, Hong

“…Cross-dataset EEG emotion recognition is an extremely challenging task, since data distributions of EEG from different datasets are greatly different, which…”
Get full text

Efficient Sample and Feature Importance Mining in Semi-Supervised EEG Emotion Recognition by Li, Xing, Shen, Fangyao, Peng, Yong, Kong, Wanzeng, Lu, Bao-Liang

“…Recently, electroencephalogram (EEG)-based emotion recognition has attracted increasing interests in research community. The weak, non-stationary, multi-rhythm…”
Get full text

Self-Supervised Learning for Sleep Stage Classification with Temporal Augmentation and False Negative Suppression by Shen, Fangyao, Zhang, Zehao, Peng, Yong, Guo, Hongjie, Chen, Lina, Gao, Hong

“…Self-supervised learning has been gaining attention in the field of sleep stage classification. It learns representations with unlabeled electroencephalography…”
Get full text

Self-Supervised Representation Learning for Sleep Stage Classification with Feature Space Augmentation and Temporal Prediction by Jiang, Qijun, Chen, Lina, Gao, Hong, Shen, Fangyao, Guo, Hongjie

“…Sleep stage classification is crucial for sleep quality assessment and disease diagnosis. While supervised methods have demonstrated good performance in sleep…”
Get full text

An Improved Feature Fusion for Speaker Recognition by Dai, Meixiang, Dai, Guojun, Wu, Yifan, Xia, Yixing, Shen, Fangyao, Zhang, Hua

“…Speech is the most effective way of communication for humans. Its uniqueness is the basis for speaker recognition. It is a research focus on finding speaker's…”
Get full text