hand detection Computer Vision Project
Here are a few use cases for this project:
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Gesture Recognition: The hand detection model could be used in applications to interpret sign language or harness control interfaces purely based on hand gestures. For example, in a smart home setting, the model could help in controlling lighting, temperature, or open curtains just through hand gestures.
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Healthcare and Rehabilitation: The model could be adopted in the health sector especially for physical rehab and patient monitoring. Tracking hand and finger movements can aid in assessing the progress of a patient's hand motor skills after an illness or injury like stroke or fractures.
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Virtual/Augmented Reality: Hand detection can be a vital component in VR/AR applications where hand movements can be used to simulate interactions with virtual objects, improving immersion and user experience.
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Robotics and Human-Machine Interaction: Use the model to improve human-robot interaction, helping robots to interpret human intentions from their hand gestures and movements.
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Security and Identification: Use the model for biometric identification systems. This could be used as an additional layer of security, recognizing individual’s unique hand ridge patterns.
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{
hand-detection-bzgxv_dataset,
title = { hand detection Dataset },
type = { Open Source Dataset },
author = { hand detection },
howpublished = { \url{ https://universe.roboflow.com/hand-detection-tqp5z/hand-detection-bzgxv } },
url = { https://universe.roboflow.com/hand-detection-tqp5z/hand-detection-bzgxv },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { mar },
note = { visited on 2024-04-25 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the hand detection project in your project.