Dataset for multiclassification of parts in industry

Published: 02-10-2019| Version 1 | DOI: 10.17632/2pvx4nwk4w.1
Herberth Fröhlich,
Natalia Grozmani,
Dominik Wolfschläeger


Data used with 5 different parts for iterative reference set creation. Images were taken with a Logitech camera from parts that were positioned on a table in different ways. It contains two folders, a development one and a test one, randomly built. This is a small dataset that suits the purpose of not using lots of data for multiclassification, which was the objective of the present work. It was shown that is possible to acquire just some relevant images from each in order to train a classifier, a feature descriptor in this case.