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Driver Dozy Discernment Using Neural Networks with SVM Variants
Muskan Kamboj
, Janaki Bhagya Sri
, Tarusree Banik
, Swastika Ojha
, Karuna Kadian
, Vimal Dwivedi
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Keyphrases
Neural Network
100%
Support Vector Machine
100%
Drowsiness
66%
India
33%
Machine Learning Algorithms
33%
Real-world Application
33%
Continuous Monitoring
33%
Eyes Open
33%
Eye Closure
33%
Effective Techniques
33%
Road Traffic Accidents
33%
Classification Methods
33%
Eye Movements
33%
Image Processing Techniques
33%
Convolutional Neural Network
33%
Further Training
33%
Accuracy Function
33%
Convolutional Neural Network Model
33%
Loss Function
33%
Lack of Concentration
33%
Driver Drowsiness
33%
Driver Drowsiness Detection
33%
Driver Distraction
33%
Closed Eyes
33%
Driver Condition
33%
Artificial Intelligence/machine Learning (AI/ML)
33%
Face Movement
33%
Driver Awareness
33%
Computer Science
Neural Network
100%
Support Vector Machine
100%
Convolutional Neural Network
66%
Machine Learning Algorithm
33%
Neural Network Model
33%
World Application
33%
Classification Technique
33%
Image Processing Technique
33%
Drowsiness Detection
33%
Artificial Intelligence
33%
Medicine and Dentistry
Convolutional Neural Network
100%
Distraction
100%
Awareness
50%
Eyelid Closure
50%
Eye Movement
50%
Artificial Intelligence
50%
Machine Learning Algorithm
50%
Material Science
Image Processing
100%