DBIS2022_P4 Object Detection Dataset and Pre-Trained Model by max kellerman

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Explore Dataset

Here are a few use cases for this project:

Grid Health Monitoring: The DBIS2022_P4 model can be used in power grid systems to automatically identify and monitor the condition of different components such as insulators, transformers, cables, etc. for damage or faults. This could significantly reduce the time and cost involved in manual inspections.
Predictive Maintenance in Power Plants: The model can be used to predict possible failure points and schedule maintenance based on subtle changes in insulators or other components. This will increase safety and efficiency in power plants.
Hardware Quality Control: Companies manufacturing power equipment can use the model to inspect their products (cables, insulators, transformers) for quality assurance purposes, identifying defective or sub-standard products.
Damage Assessment during Natural Disasters: The model can assist in doing swift and accurate damage assessment of power infrastructure after natural disasters such as hurricanes and earthquakes, helping in prioritizing repairs and restoration of normal power supply.
Electrician Training: The model could serve as a training aid for new electricians or electrical engineers, helping them understand different components and identify common issues like a bent insulator, frayed cable, or burned transformer.

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{
                            dbis2022_p4_dataset,
                            title = { DBIS2022_P4 Dataset },
                            type = { Open Source Dataset },
                            author = { max kellerman },
                            howpublished = { \url{ https://universe.roboflow.com/max-kellerman-cz98k/dbis2022_p4 } },
                            url = { https://universe.roboflow.com/max-kellerman-cz98k/dbis2022_p4 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-05-02 },
                            }