Data supporting: 'Autonomous Ground Refuelling Approach for Civil Aircrafts using Computer Vision and Robotics' - Yildirim, Suleyman (Cranfield University, 2022)
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
Keywords: aircraft refuelling adaptor'; 'pressurised refuelling adaptor'