English

Industrial Machine Tool Component Surface Defect Dataset

Computer Vision and Pattern Recognition 2022-02-22 v1 Image and Video Processing

Abstract

Using machine learning (ML) techniques in general and deep learning techniques in specific needs a certain amount of data often not available in large quantities in technical domains. The manual inspection of machine tool components and the manual end-of-line check of products are labor-intensive tasks in industrial applications that companies often want to automate. To automate classification processes and develop reliable and robust machine learning-based classification and wear prognostics models, one needs real-world datasets to train and test the models. The dataset is available under https://doi.org/10.5445/IR/1000129520.

Keywords

Cite

@article{arxiv.2103.13003,
  title  = {Industrial Machine Tool Component Surface Defect Dataset},
  author = {Tobias Schlagenhauf and Magnus Landwehr and Juergen Fleischer},
  journal= {arXiv preprint arXiv:2103.13003},
  year   = {2022}
}

Comments

7 pages, 13 figures

R2 v1 2026-06-24T00:30:08.485Z