Improving Distinguishability of Photoplethysmography in Emotion Recognition Using Deep Convolutional Generative Adversarial Networks
We propose an emotion recognition framework based on ResNet, bidirectional long- and short-term memory (BiLSTM) modules, and data augmentation using a ResNet deep convolutional generative adversarial network (DCGAN) with photoplethysmography (PPG) signals as input. The emotions identified in this st...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9947048/ |