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galvanized-636 – A galvanized steel re-identification dataset

Authors: Rutinowski, Jérôme; Endendyk, Jan; Reining, Christopher; Roidl, Moritz;

galvanized-636 – A galvanized steel re-identification dataset

Abstract

The dataset "galvanized-636" contains images of 636 sheets of galvanized steel, of which four pictures each were taken per side from different, labeled perspectives, amounting to a total of 5,088 images. This dataset can be used for the purpose of re-identification. Therefore, if you use this dataset for research, please cite us using the Zenodo DOI. The recording specifications are the following: Camera: Canon EOS 6D (with ambient lighting: ISO 1600; white balance; 1/50 shutter; F22 aperture. With photography lighting: ISO 1600; 1/30 shutter; F22 aperture) Naming convention: first integer = number of metal sheet (ms); f = front; b = back; AL = ambient lighting; PL = photography lighting; 75/90 = recording angle Images per sheet: Combination of AL/PL + 75°/90° --> 4 images per sheet The predecessors of this dataset are "pallet- block-502" and "pallet-block-32965". If you have any questions concerning these datasets, feel free to contact the corresponding author, Jérôme Rutinowski. This work is part of the project "Silicon Economy Logistics Ecosystem" which is funded by the German Federal Ministry of Transport and Digital Infrastructure.

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Keywords

re-identification, deep learning, galvanized steel, industrial dataset

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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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