xatrungthe Object Detection Dataset and Pre-Trained Model by xatrungthe

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4767 images

Explore Dataset

Here are a few use cases for this project:

Utility Line Inspection: This model can be used to grow routine maintenance efficiency of power lines, especially in remote locations. Aerial imagery could be analyzed by the model to recognize power lines over ponds, lakes, or other natural landscapes, aiding professionals in pinpointing potential problems or areas that need repair.
Environmental Planning: The model could be deployed for planning landscape conservation projects. It can help differentiate between areas that have power lines running through them, and those without, aiding in their planning to ensure minimal disruption to local ecosystems.
Drone Navigation: The "xatrungthe" model can be integrated into drone technology to identify power lines over ponds and other bodies of water, enabling safer and more efficient path planning and navigation.
Wildlife Conservation: This model can be used to identify areas where power lines may pose a risk to bird life or other flying creatures, providing useful data for conservation efforts.
Emergency Services: In the event of natural disasters or emergencies, the model can quickly identify the location of power lines over various landscapes, assisting emergency services in their assessments and responses.

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{
                            xatrungthe_dataset,
                            title = { xatrungthe Dataset },
                            type = { Open Source Dataset },
                            author = { xatrungthe },
                            howpublished = { \url{ https://universe.roboflow.com/xatrungthe/xatrungthe } },
                            url = { https://universe.roboflow.com/xatrungthe/xatrungthe },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-04-29 },
                            }