KunAmn2023_0194 Computer Vision Project
Here are a few use cases for this project:
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Driver Safety: The model can be used by car manufacturers to develop advanced driving assistant systems (ADAS) that monitor drivers for signs of drowsiness and trigger warning signs, thereby enhancing road safety.
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Fatigue Monitoring in Workplace: Industrial companies can use the model to ensure the fitness and alertness of operators in high-risk environments like mining, nuclear power plants, and manufacturing units where fatigue-related accidents could have serious implications.
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Health Monitoring: It can be incorporated in wellness apps or wearable devices to monitor users for signs of fatigue, advising them to take breaks, rest, or sleep, promoting personal health management.
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Educational Tools: The model can be utilized in online learning platforms to identify if the student is attentive or fatigued, shaping personalized learning processes and offering breaks when needed.
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Drowsiness Detection in Aviation: Airlines can use the model's capability to monitor pilots and air traffic controllers for signs of fatigue, ensuring safe air travel.
Trained Model API
This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
kunamn2023_0194_dataset,
title = { KunAmn2023_0194 Dataset },
type = { Open Source Dataset },
author = { class },
howpublished = { \url{ https://universe.roboflow.com/class-wz5a4/kunamn2023_0194 } },
url = { https://universe.roboflow.com/class-wz5a4/kunamn2023_0194 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { feb },
note = { visited on 2024-04-26 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the KunAmn2023_0194 project in your project.
