Electric-Pylon-Detection-in-RSI Computer Vision Project

Robin Public

Updated 2 years ago

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Description

From the Authors:

EPD dataset contains 1500 images in total: 720 images were captured by Pleiades satellite along Huimao Line in Guangdong Province, China, a main line of power network in south China, while the remaining images were collected from Google Earth to further improve the representativeness of the dataset by expanding the source of samples. The spatial resolution of images in EPD dataset is 1 m/pixel.

Moreover, to test and evaluate the adaptability of the detectors in face of actual situations, we specially selected 50 relatively complex images from EPD dataset comprising a complex test subset called EPD-C ...

1450 images in EPD dataset excluding EPD-C as a standard subset named EPD-S, which involves more than 3000 electric pylons. EPD-S subset was used to train detectors and perform random experiments.

Dataset Source:

This dataset is obtained from the listing in Robin Cole's satellite-image-deep-learning GitHub repository

Electric-Pylon-Detection-in-RSI -> a dataset which contains 1500 remote sensing images of electric pylons used to train ten deep learning models

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            electric-pylon-detection-in-rsi_dataset,
                            title = { Electric-Pylon-Detection-in-RSI Dataset },
                            type = { Open Source Dataset },
                            author = { Robin Public },
                            howpublished = { \url{ https://universe.roboflow.com/robin-public/electric-pylon-detection-in-rsi } },
                            url = { https://universe.roboflow.com/robin-public/electric-pylon-detection-in-rsi },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { dec },
                            note = { visited on 2024-11-22 },
                            }
                        
                    

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