segmentation Instance Segmentation Dataset and Pre-Trained Model by ENIM

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Explore Dataset

Here are a few use cases for this project:

Infrastructure Maintenance: The segmentation model can be used to identify and classify different types of cracks in public infrastructure like buildings, bridges, roads, and railways. This could assist in early detection and maintenance, preventing costly repairs or accidents.
Geology and Environmental Studies: The model could be used to analyze cracks in the ice in the polar regions, assisting in climate research by monitoring the melting rate of glaciers and its impact on sea levels.
Automotive Industry: The model can be used in the analysis of wear and tear in vehicles, particularly in tires where cracks could lead to potentially dangerous blowouts.
Aerospace Industry: The model can be used to detect cracks in aircraft fuselage or wings during routine maintenance checks. Early detection will reduce the risk of catastrophic failure during flights.
Energy Industry: In wind turbine maintenance, the model could be used to detect cracks in turbine blades. Early detection can prevent failures, prolonging the lifespan of the turbines and increasing efficiency.

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{
                            segmentation-l6ldj_dataset,
                            title = { segmentation Dataset },
                            type = { Open Source Dataset },
                            author = { ENIM },
                            howpublished = { \url{ https://universe.roboflow.com/enim-lmuhi/segmentation-l6ldj } },
                            url = { https://universe.roboflow.com/enim-lmuhi/segmentation-l6ldj },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-05-07 },
                            }