Convolution Neural Networks for Person Identification and Verification Using Steady State Visual Evoked Potential

Keyphrases

• Person Identification 100%
• Human Verification 100%
• Steady-state Visual Evoked Potential (SSVEP) 100%
• Convolution Neural Network 100%
• Feature Extraction Methods 20%
• Biometric System 20%
• Biometric Data 20%
• Canonical Correlation Analysis 20%
• False Acceptance Rate 20%
• Biometrics 20%
• Verification Accuracy 20%
• Deep Learning 20%
• Limited Range 20%
• Feature Correlation Analysis 20%
• EEG Signals 20%
• Raw Signal 20%
• Biometric Signals 20%
• Brain Activity 20%
• Identification Accuracy 20%
• Comprehensive Comparison 20%
• Specific Frequency 20%
• Handcrafted Features 20%
• Visual Stimulation 20%
• Acceptance Rate 20%
• Unique Information 20%
• Real-time Embedded Systems 20%
• Power Spectrum Feature 20%

Computer Science

• Convolutional Neural Network 100%
• Biometrics 66%
• Biometric System 33%
• Correlation Analysis 33%
• Feature Extraction 33%
• False Acceptance Rate 33%
• Biometric Information 33%
• Embedded System 33%
• Brain Activity 33%
• Deep Learning Method 33%
• Preprocessing 33%
• Acceptance Rate 33%
• Unique Information 33%

Neuroscience

• Neural Network 100%
• Visual Evoked Potential 100%
• Electroencephalogram 20%