Drowsiness Detection Dataset

Drowsiness Detection Dataset

Datasets

Drowsiness Detection Dataset

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Drowsiness Detection Dataset

Use Case

Driver Safety

Description

A Drowsiness Detection Dataset is a collection of data specifically curated for developing and evaluating machine learning algorithms and computer vision models aimed at detecting drowsiness or fatigue in individuals, particularly in the context of activities like driving or operating heavy machinery. Detecting drowsiness is crucial for preventing accidents and ensuring safety in various scenarios.

 

Drowsiness Detection Dataset

About Dataset

At our AI data collection company, we’re excited to introduce the UnityEyes  Dataset. This dataset is a valuable resource for researchers and developers working on spotting tired drivers, especially by studying their eye movements. We used UnityEyes, a high-quality eye simulation software, to gather the data, ensuring its accuracy and reliability. Each snapshot in the dataset is carefully labeled to indicate whether the eyes are open or closed, which is crucial for identifying sleep-deprived drivers.

The Sleepy Driver Dataset is packed with various eye movement data from folks of all backgrounds, gathered while they were behind the wheel in regulated driving situations. This dataset brims with snapshots of eyes, each precisely tagged to tell us whether they’re open or closed – a critical tool in identifying sleep-deprived drivers.

 

Conclusion

Globose Technology Solutions Private Limited is a leader in drowsiness detection technology, leveraging insights from the Drowsiness Detection Dataset. Our advanced algorithms enable real-time identification of drowsiness, improving safety in transportation and workplaces. Committed to creating a safer environment, Globose is at the forefront of advancing drowsiness detection across various domains.

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