Proyecto linderos Semantic Segmentation Dataset and Pre-Trained Model by Linderos

Images

512 images

Explore Dataset

Here are a few use cases for this project:

Land Surveying: The model can assist surveyors in identifying boundaries, roadways, and canals for use in mapping, planning, and property delineation. In large-scale surveys, this can save time and reduce human error.
Farm Management: For large-scale farmers, the model can help in identifying and categorizing land features. This information can be used to plan efficient usage of farm equipment, irrigation systems, or crop distribution.
Environmental Studies: Researchers can use the model to study patterns in land use and transformation, tracking the existence and changes in canal networks, roads, and land borders over time.
Infrastructure Planning: City or infrastructure planners can utilize the model to detect existing boundaries and pathways, guiding decisions on construction projects, road networks, or canal restorations.
Emergency Services: In case of natural disasters, this model can help relief agencies with rapid assessment of accessible roads and potential barriers like fences or canals, providing crucial information for planning rescue and relief operations.

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{
                            proyecto-linderos_dataset,
                            title = { Proyecto linderos Dataset },
                            type = { Open Source Dataset },
                            author = { Linderos },
                            howpublished = { \url{ https://universe.roboflow.com/linderos/proyecto-linderos } },
                            url = { https://universe.roboflow.com/linderos/proyecto-linderos },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jul },
                            note = { visited on 2024-05-17 },
                            }