EE297_Project Object Detection Dataset and Pre-Trained Model by EE297

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Explore Dataset

Here are a few use cases for this project:

Smart Waste Sorting: Use EE297_Project as the core engine for developing an automated waste sorting system implemented in residential or commercial areas, which ensures that waste items are accurately classified into their respective disposal containers (Paper, Plastic, Glass, Metal, Cardboard).
Environmental Cleanup Assistance: Integrate EE297_Project into mobile applications or drones to help quickly identify waste items during community clean-up events, assisting volunteers in efficiently picking up and properly disposing of waste to reduce environmental impact.
Recycling Industry Optimization: Employ EE297_Project to streamline recycling plant operations, enabling more effective identification and separation of different waste materials in real-time, ultimately leading to a more efficient recycling process.
Waste Collection Route Optimization: Utilize EE297_Project to analyze and identify the presence of waste in multiple locations through a city, helping waste management companies optimize their collection routes and schedules based on the presence and types of waste in different areas.
Educational Tool: Integrate EE297_Project into interactive educational installations or applications to teach about proper waste disposal and the importance of recycling. Users can test their knowledge and learn in real-time how to correctly classify various waste items.

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{
                            ee297_project_dataset,
                            title = { EE297_Project Dataset },
                            type = { Open Source Dataset },
                            author = { EE297 },
                            howpublished = { \url{ https://universe.roboflow.com/ee297/ee297_project } },
                            url = { https://universe.roboflow.com/ee297/ee297_project },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { jul },
                            note = { visited on 2024-04-26 },
                            }