Tailings Object Detection Dataset and Pre-Trained Model by Tailings

Images

1263 images

Explore Dataset

Here are a few use cases for this project:

Environmental Monitoring: Using the "Tailings" computer vision model, researchers and environmental agencies can monitor tailings ponds and their impact on the surrounding ecosystem. By automating the identification of tailings storage facilities in aerial images, they can track their growth or decline and assess the risk of leakage or containment failures.
Mining Industry Compliance: Regulatory bodies can use the "Tailings" model to ensure that mining companies are adhering to safety and environmental standards in the management of their tailings storage facilities. By identifying tailings in aerial images, they can conduct remote inspections and identify potential violations.
Land Reclamation Planning: After a mine has been closed, the land needs to be restored to a safe and usable condition. The "Tailings" model can help professionals in the field of land reclamation to identify and monitor tailings deposits, enabling them to develop and implement effective remediation plans.
Tailings Dam Safety Assessment: Engineers and safety experts can use the "Tailings" computer vision model to assess the stability and safety of tailings dams. By detecting signs of compromise in the structural integrity of tailings storage facilities, they can proactively address potential hazards and prevent catastrophic failures.
Environmental Impact Studies: Environmental consultants and researchers can employ the "Tailings" model to study the impact of mining operations on local ecosystems, water resources, and wildlife. By identifying tailings deposits in remote sensing images, they can track and assess the spread of pollutants and the effectiveness of containment systems.

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{
                            tailings_dataset,
                            title = { Tailings Dataset },
                            type = { Open Source Dataset },
                            author = { Tailings },
                            howpublished = { \url{ https://universe.roboflow.com/tailings/tailings } },
                            url = { https://universe.roboflow.com/tailings/tailings },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { jul },
                            note = { visited on 2024-04-26 },
                            }