Code to paper: Review of image segmentation techniques for the layup defect detection in the Automated Fiber Placement process
doi:10.4121/14412923.v1
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doi: 10.4121/14412923
doi: 10.4121/14412923
Datacite citation style:
Sebastian Meister; Mahdieu Wermes (2021): Code to paper: Review of image segmentation techniques for the layup defect detection in the Automated Fiber Placement process. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/14412923.v1
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Software
This code was used to generate the results for the paper
"Review of image segmentation techniques for the layup defect
detection in the Automated Fiber Placement process"
"Review of image segmentation techniques for the layup defect
detection in the Automated Fiber Placement process"
history
- 2021-05-11 first online, published, posted
publisher
4TU.ResearchData
associated peer-reviewed publication
Review of image segmentation techniques for layup defect detection in the Automated Fiber Placement process
funding
- German Aerospace Center core funding
organizations
TU Delft, Faculty of Aerospace Engineering, Department of Aerospace Structures & Materials;German Aerospace Center (DLR), Center for Lightweight Production Technology (ZLP)
DATA
files (6)
- 2,204 bytesMD5:
0f5b8c096cc095bde2f9361a7f059843
README.txt - 7,020 bytesMD5:
f9dc661f840c61c172ddc474c3a66cf6
cfg_gen.py - 2,150 bytesMD5:
409f53c18ec491d52fbc36234bcd13a4
config.ini - 3,773 bytesMD5:
5d80a316a1fc2728e43cd7ec898e4a64
DefectDetectionAnalysis.py - 1,169 bytesMD5:
a5a1ff69de1c48bc16b5a711d7cd8548
instructions.ini - 10,782 bytesMD5:
cf94031d2790bbfead69a5f79297f0d7
newstyle_DefectDetectionAnalysis.py -
download all files (zip)
27,098 bytes unzipped