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IEEE/ICACT20210194 Slide.16        [Big Slide]	Oral Presentation
	It was found that pre-trained deep learning models on the ImageNet dataset can be fine-tuned to improve the accuracy to classify State Farm distracted driver dataset. Three architectures and their weights were used and applied three different freezing techniques on the layers making them overall nine models. After re-training models with distracted drivers image dataset, they are evaluated by predicting 500 unseen test sets. As a result, Mobile Net model_2 showed the best 99% accuracy. It is recommended that this model could be used in real-time environments.

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