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Varshitha S presented on detecting driver drowsiness using convolutional neural networks. The objective was to develop a lightweight yet high-performance system to detect drowsiness based on facial landmarks analyzed by a CNN model. The methodology used the NTHU dataset, data augmentation, and a Dlib library to extract facial landmarks as input to a CNN with ReLU layers and max pooling. Testing achieved an accuracy of 83.3% for drowsiness detection across categories, an improvement over prior MLP methods. T

Author

Swathi Reddy

Language

EN