Optimizing Input for Gesture Recognition using Convolutional Networks on HD-sEMG Instantaneous Images

Keyphrases

• High-density Surface Electromyography 100%
• Convolutional Networks 100%
• Gesture Recognition 100%
• Preprocessing Techniques 42%
• Surface Electromyography (sEMG) 42%
• Monopolar 28%
• Convolutional Neural Network 28%
• High Temporal Resolution 14%
• Classification Accuracy 14%
• Prediction Accuracy 14%
• Laplacian 14%
• Input Signals 14%
• Spatio-temporal Features 14%
• Validation Accuracy 14%
• Hand Gesture Recognition 14%

Computer Science

• Electromyography 100%
• Convolutional Network 100%
• Gesture Recognition 100%
• Convolutional Neural Network 28%
• Preprocessing Technique 28%
• Preprocessing Step 14%
• Laplace Operator 14%
• Classification Accuracy 14%
• Temporal Resolution 14%
• Prediction Accuracy 14%
• Temporal Feature 14%
• hand gesture recognition 14%

Earth and Planetary Sciences

• Preprocessing 100%