Data supporting: 'Autonomous Ground Refuelling Approach for Civil Aircrafts using Computer Vision and Robotics'

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2022-08-15 09:05

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Cranfield University

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Yildirim, Suleyman (2022). Data supporting: 'Autonomous Ground Refuelling Approach for Civil Aircrafts using Computer Vision and Robotics'. Cranfield Online Research Data (CORD). Dataset. https://doi.org/10.17862/cranfield.rd.20445579

Abstract

Aircraft Refuelling Adaptor Localisation - v3 2022-03-15 12:35pm It includes 881 images. Letters are annotated in COCO format. The following pre-processing was applied to each image: The following augmentation was applied to create 3 versions of each source image: * 50% probability of horizontal flip * 50% probability of vertical flip * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down * Random Gaussian blur of between 0 and 1 pixels

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Github

Keywords

aircraft refuelling adaptor', 'pressurised refuelling adaptor'

DOI

10.17862/cranfield.rd.20445579

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CC BY 4.0

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