On Fatigue Detection for Air Traffic Controllers Based on Fuzzy Fusion of Multiple Features

Keyphrases

• Multi-feature 100%
• Facial Features 100%
• Air Traffic Controller 100%
• Fuzzy Fusion 100%
• Fatigue Detection 100%
• Blinking 75%
• Voice Features 75%
• Detection Method 50%
• Convolutional Neural Network 50%
• Challenging Problems 25%
• Single Model 25%
• Eye Closure 25%
• Detection Accuracy 25%
• Open Mouth 25%
• Real-world Experiment 25%
• Safety Research 25%
• First Use 25%
• Air Traffic Management 25%
• Eye Area 25%
• Mouth Area 25%
• Multi-feature Fusion 25%
• Ensemble Learning Model 25%
• Voice Design 25%
• Stacking Model 25%
• Stacking Method 25%
• Dlib 25%
• Percentage of Eye Closure (PERCLOS) 25%
• China Civil Aviation 25%
• Mel Frequency Cepstral Coefficient Features 25%
• Aviation Safety 25%
• Mouth Closure 25%
• Eyelid Closure 25%
• OpenCV Library 25%

Computer Science

• Facial Feature 100%
• Detection Method 50%
• Convolutional Neural Network 50%
• Traffic Management 25%
• Detection Accuracy 25%
• Ensemble Learning 25%
• Mel Frequency Cepstral Coefficient 25%