Trash Detection Computer Vision Project

PLM Thesis

Updated 2 years ago

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littering
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Description

Here are a few use cases for this project:

  1. Litter Monitoring - This model can be used by environmental services or urban planning departments to monitor and track trash levels in public spaces, so they can optimize cleaning and maintenance schedules.

  2. CSR Initiatives - Corporate entities aiming for sustainability goals can use this model in their CSR initiatives, for instance, to assess and demonstrate the impact of their clean-up efforts in public spaces or water bodies.

  3. Waste Management - Waste management companies can use this model to automate the identification and segregation of waste materials, leading to increased recycling rates.

  4. Public Awareness Campaigns - Government and non-profit organizations can use this model in public awareness campaigns, showing real-time litter conditions in various locations to encourage people to litter less and maintain cleanliness.

  5. Surveillance Systems - Surveillance camera systems can utilize this model to detect and notify when littering occurs in monitored areas such as parks, commercial properties, and city streets, allowing for quick response.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            trash-detection-k8zqx_dataset,
                            title = { Trash Detection Dataset },
                            type = { Open Source Dataset },
                            author = { PLM Thesis },
                            howpublished = { \url{ https://universe.roboflow.com/plm-thesis-kefnj/trash-detection-k8zqx } },
                            url = { https://universe.roboflow.com/plm-thesis-kefnj/trash-detection-k8zqx },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-12-23 },
                            }
                        
                    

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