waste Instance Segmentation Dataset and Pre-Trained Model by JU

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Explore Dataset

Here are a few use cases for this project:

Waste Management Automation: The computer vision model could be used to automate the process of waste sorting and management in recycling facilities, enhancing efficiency and reducing human labor.
Smart City Initiatives: Urban municipalities could use the model within smart bins or waste collection vehicles to identify and track the type of waste that is being disposed of, helping to improve recycling rates, optimize waste collection routes and manage the urban waste stream more effectively.
Environmental Studies: Environmental scientists or researchers could use the model to study the distribution and types of waste in different habitats - urban cities, forests, oceans, etc., playing a key role in understanding the impact of waste and designing effective mitigation strategies.
Consumer Awareness Campaigns: This model could be used in apps or websites, enabling consumers to easily identify waste types and understand how to dispose of them properly, thus promoting environmental sustainability and responsible consumption.
Retail & Manufacturing Industries: Businesses can use this model to assess the types of waste produced in their operations, helping them to reduce waste and making them more environmentally friendly and sustainable.

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{ waste-gqtlh_dataset,
    title = { waste Dataset },
    type = { Open Source Dataset },
    author = { JU },
    howpublished = { \url{ https://universe.roboflow.com/ju-uveje/waste-gqtlh } },
    url = { https://universe.roboflow.com/ju-uveje/waste-gqtlh },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { may },
    note = { visited on 2023-12-11 },
}