KAB-ML Computer Vision Project
Updated 3 years ago
Metrics
Here are a few use cases for this project:
-
Smart Waste Management: KAB-ML can be used by municipal waste management departments to categorize and identify litter in public spaces, allowing them to prioritize cleaning and maintenance schedules based on the density and types of trash found in different areas.
-
Environmental Monitoring: NGOs and environmental organizations can use this model to track and analyze litter distribution in urban and natural environments, helping them understand the sources of pollution and develop targeted campaigns to reduce littering.
-
Robotic Trash Picker: KAB-ML can be integrated into robotic systems designed to autonomously collect and dispose of trash in public areas such as parks, streets, and beaches. The model can enable the robot to recognize various types of litter, improving its efficiency in picking up and handling waste.
-
Public Awareness Campaigns: Governments and organizations can use the model's findings to create data-driven awareness campaigns that highlight the most pressing litter issues in a specific area, motivating citizens to take action and keep their communities clean.
-
Monitoring Waste Disposal Compliance: KAB-ML can be employed to evaluate and monitor the effectiveness of waste disposal programs, such as recycling and composting, by analyzing the types of litter found in specific locations. This information can be used to identify areas where compliance is low and develop strategies to improve adherence to waste disposal guidelines.
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{
kab-ml_dataset,
title = { KAB-ML Dataset },
type = { Open Source Dataset },
author = { Old Dataset },
howpublished = { \url{ https://universe.roboflow.com/old-dataset/kab-ml } },
url = { https://universe.roboflow.com/old-dataset/kab-ml },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { apr },
note = { visited on 2024-11-22 },
}