Müll Computer Vision Project
Updated a year ago
249
views17
downloadsMetrics
Here are a few use cases for this project:
-
Waste Segregation Systems: Automated recycling machines or systems can use the Müll model to identify and sort different types of waste accurately, speeding up the recycling process.
-
Smart Cities: The model can be integrated into smart city programs to monitor littering hotspots, identify the types of trash commonly found, and help design targeted clean-up initiatives.
-
Recycling Education: Educational institutions or environmental organizations can use the model as part of interactive exhibits or learning applications to educate the public on various types of waste and their respective disposal methods.
-
Autonomous Cleaning Robots: Developing smart robots or drones capable of picking up and sorting litter in public spaces, parks, and streets, making these clean-up mechanisms more efficient.
-
Industrial Waste Management: Companies could use the model to correctly identify and sort waste produced in their facilities, ensuring accurate disposal or recycling processes, and potentially reducing waste management costs.
Use This Trained Model
Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
mull_dataset,
title = { Müll Dataset },
type = { Open Source Dataset },
author = { Severin Kunz },
howpublished = { \url{ https://universe.roboflow.com/severin-kunz-nyjja/mull } },
url = { https://universe.roboflow.com/severin-kunz-nyjja/mull },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { dec },
note = { visited on 2024-12-22 },
}