Railway fastening clips dataset wth fastclip Railway fastening clips dataset wth fastclip 2024-387-1 https://doi.org/10.5878/cnd4-fs77 Swedish National Data Service Svensk nationell datatjänst Landing page Railway fastening clips dataset wth fastclip Railway fastening clips dataset wth fastclip 2024-387-1 https://doi.org/10.5878/cnd4-fs77 10.1109/I2MTC53148.2023.10176099 urn:nbn:se:miun:diva-49092 Shallari, Irida Shallari, Irida Swedish National Data Service Svensk nationell datatjänst Landing page railway transport järnvägstransport railway tracks rälsar Railway fastening clips dataset wth fastclip. This record contains a dataset with the railway fastening clip called fastclip and the installation datasheet for the same clip provided by the clip manufacturer, Pandrol AB. The railway_dataset folder contains three subfolders: - The calibration folder, where are the images taken at angles from 0–30 with a step of 3 degrees. - The test and the validation folder, where are the images and their respective labels based on the YOLO Oriented Bounding Box method. The fastclip datasheet document is an installation sheet provided from the manufacturer of the fastclip, Pandrol AB. The dataset was originally published in DiVA and moved to SND in 2024. Numeric Text Still image Access to data through SND. Data are freely accessible. Åtkomst till data via SND. Data är fritt tillgängliga. openAccess V. Gallo, I. Shallari, M. Carratu and M. O'Nils, "Metrological Characterization of a Clip Fastener assembly fault detection system based on Deep Learning," 2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Kuala Lumpur, Malaysia, 2023, pp. 1-6, doi: 10.1109/I2MTC53148.2023.10176099. V. Gallo, I. Shallari, M. Carratu and M. O'Nils, "Metrological Characterization of a Clip Fastener assembly fault detection system based on Deep Learning," 2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Kuala Lumpur, Malaysia, 2023, pp. 1-6, doi: 10.1109/I2MTC53148.2023.10176099. 10.1109/I2MTC53148.2023.10176099 urn:nbn:se:miun:diva-49092 2023