Open Access

Classification of gravure printed patterns using singular value decomposition and machine learning (MATLAB code)

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Files

README_MachLearn_ImgClass.txt () (10.03 KB)
 code_MachLearn_ImgClass.zip () (269.47 MB)
 dots_all.mat () (4.34 GB)
 fingers_all.mat () (6.41 GB)
 mixed_all.mat () (1.74 GB)

Date

2023-05-16

Type

Text
Software
Image
Other

Authors

Rothmann-Brumm, PaulineORCID 0000-0002-8220-0676

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

Description

This dataset contains MATLAB code ('code_MachLearn_ImgClass.zip') for automated classification of gravure printed patterns from the [HYPA-p](https://doi.org/10.48328/tudatalib-1150) dataset. The developed algorithm performs singular value decomposition (SVD) and training of several machine learning classifiers, such as k-Nearest Neighbors (kNN). The classifiers are trained and tested on labeled data. Afterwards, the trained classifiers can be used for automated classification of unlabeled data. Further information can be found in the provided README-file.

Keywords

MATLAB code, reduced-order modeling, pattern classification, singular value decomposition, machine learning, gravure printing, hydrodynamic pattern formation

Citation

Identifier

https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/3843
 https://doi.org/10.48328/tudatalib-1152

Endorsement

DFG Classification

4.21-03 Mechanische Verfahrenstechnik
4.22-03 Strömungsmechanik
4.31-03 Beschichtungs- und Oberflächentechnik

Project(s)

DFG | SFB1194 | TP C01 Dörsam

Faculty

Collections

License

CC-BY-NC 4.0 - Attribution-NonCommercial 4.0 International
Except where otherwise noted, this license is described as CC-BY-NC 4.0 - Attribution-NonCommercial 4.0 International