High-Fidelity Emotion Recognition via SDR-Based Wireless Sensing and Deep Learning

Keyphrases

• Software Defined Radio 100%
• Deep Learning 100%
• Emotion Recognition 100%
• Human Emotion Recognition 100%
• Wireless Sensing 100%
• Human Activities 66%
• Non-contact 66%
• Human Gesture 66%
• Happiness 33%
• Anger 33%
• Laboratory Environment 33%
• Classification Accuracy 33%
• Orthogonal Frequency Division multiplexing 33%
• Transceiver 33%
• Facial Expression 33%
• Recognition Method 33%
• Sadness 33%
• Text-to-speech 33%
• Emotional State 33%
• Recall Score 33%
• Precision Score 33%
• Physiological Signals 33%
• Gated Recurrent Unit 33%
• F1 Score 33%
• Human Emotions 33%
• Precision-recall 33%
• Personal Perception 33%
• Deep Learning Algorithm 33%
• Innovative Methods 33%
• Recurrent Neural Network-long Short-term Memory 33%
• Precision Accuracy 33%
• Speech Signal 33%
• Accuracy Measure 33%
• Deep Learning Framework 33%
• Activity Sensing 33%
• Disgust 33%
• Radio Time 33%
• Simple Recurrent Network 33%
• Radio Frequency Technology 33%
• Internal Senses 33%
• Sequential Deep Learning Model 33%
• Bidirectional Gated Recurrent Unit (BiGRU) 33%
• Radiofrequency 33%
• Bidirectional Long Short-Term Memory (BiLSTM) 33%
• Wireless Channel Information 33%

Computer Science

• software-defined radio 100%
• Deep Learning Method 100%
• Recurrent Neural Network 33%
• Collected Data 33%
• Laboratory Environment 33%
• Wireless Channel 33%
• Orthogonal Frequency Division Multiplexing 33%
• Channel State Information 33%
• Classification Accuracy 33%
• Facial Expression 33%
• Learning Framework 33%
• Emotional State 33%
• Physiological Signal 33%
• Long Short-Term Memory Network 33%
• Deep Learning Model 33%
• Bidirectional Long Short-Term Memory Network 33%
• Gated Recurrent Unit 33%
• Bi-Directional Gated Recurrent Unit 33%