KickboardDetection_1 Object Detection Dataset and Pre-Trained Model by CapstonDesign

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Explore Dataset

Here are a few use cases for this project:

Child Safety: This model can be used in public parks or playgrounds to monitor safety compliance among children who use kickboards. With its ability to differentiate between users who wear helmets (helmetO) and those who don't (helmetX), it can alert supervising adults about children not wearing helmets for immediate action.
Kickboard Design Analog/Digital Inventory: Retailers and manufacturers can use the model in helping them to categorize their kickboard products (swingW, fellow, xingxing, alpaca, personal) more effectively, assist in inventories and improve organization of stock.
Augmented Reality Gaming: In an augmented reality game where users drive kickboards, this model can recognize and differentiate between different kickboard classes providing a unique in-game experience depending on the type of kickboard.
Surveillance in Recreational Facilities: The model can be used in surveillance systems at recreational facilities or skate parks to monitor and record the different types of kickboards in use. It can provide useful data to administrative personnel in managing such facilities
Automated Shopping Experience: In a smart store setting, it can identify different types of kickboards to provide information, suggestions, or specific promotions to the customer in real-time. Based on what type of kickboard a customer shows interest in, the model can trigger targeted advertisements or promotions.

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{ kickboarddetection_1_dataset,
    title = { KickboardDetection_1 Dataset },
    type = { Open Source Dataset },
    author = { CapstonDesign },
    howpublished = { \url{ https://universe.roboflow.com/capstondesign/kickboarddetection_1 } },
    url = { https://universe.roboflow.com/capstondesign/kickboarddetection_1 },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { apr },
    note = { visited on 2023-12-02 },
}