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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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HRPlanesv2 - High Resolution Satellite Imagery for Aircraft Detection

Authors: Unsal, Dilsad;

HRPlanesv2 - High Resolution Satellite Imagery for Aircraft Detection

Abstract

The HRPlanesv2 dataset contains 2120 VHR Google Earth images. To further improve experiment results, images of airports from many different regions with various uses (civil/military/joint) selected and labeled. A total of 14,335 aircrafts have been labelled. Each image is stored as a ".jpg" file of size 4800 x 2703 pixels and each label is stored as YOLO ".txt" format. Dataset has been split in three parts as 70% train, %20 validation and test. The aircrafts in the images in the train and validation datasets have a percentage of 80 or more in size.

{"references": ["https://eod-grss-ieee.com/dataset-detail/ak1BclhJbkpuUkh5Uitmd3B5L2hNQT09", "https://github.com/dilsadunsal/HRPlanesv2-Data-Set"]}

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Keywords

aircraft detection, remote sensing, object detection, earth observation, artificial intelligence, airplane detection, object detection from satellite imagery

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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