waste Semantic Segmentation Dataset and Pre-Trained Model by project-qjcim

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Explore Dataset

Here are a few use cases for this project:

Smart Waste Management System: Implement the "waste" computer vision model in waste management facilities or smart trash bins to automatically sort and separate different types of waste for recycling, composting, or proper disposal, making rubbish collection and processing more efficient.
Environmental Monitoring and Cleanup: Integrate the "waste" model into drones or autonomous robots for monitoring public spaces such as parks, beaches, and streets, identifying waste items in real-time, and aiding in cleanup efforts to prevent littering and maintain a clean environment.
Educational Tool for Waste Awareness: Use the "waste" computer vision model as part of an interactive mobile app or game that helps users learn about waste classification, recycling, and proper waste disposal, promoting environmental awareness and encouraging responsible waste management habits.
Retail Stock Management: Deploy the "waste" model to monitor retail stores' inventory and identify damaged or unusable items for swift removal and replacement, ensuring product quality and reducing the risk of selling faulty goods to customers.
Waste Reduction Assessment: Integrate the "waste" computer vision model with video surveillance systems in industrial, commercial, or institutional settings to monitor waste generation, identify frequent waste items, and provide insights on waste reduction strategies and sustainable practices.

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-3bksx_dataset,
                            title = { waste Dataset },
                            type = { Open Source Dataset },
                            author = { project-qjcim },
                            howpublished = { \url{ https://universe.roboflow.com/project-qjcim/waste-3bksx } },
                            url = { https://universe.roboflow.com/project-qjcim/waste-3bksx },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-05-10 },
                            }