---
res:
  bibo_abstract:
  - Due to their cost-efficiency and environmental friendliness, the demand of mechanical
    joining processes is constantly rising. However, the dimensioning and design of
    joints and suitable processes are mainly based on expert knowledge and few experimental
    data. Therefore, the performance of numerical and experimental studies enables
    the generation of optimized joining geometries. However, the manual evaluation
    of the results of such studies is often highly time-consuming. As a novel solution,
    image segmentation and machine learning algorithm provide methods to automate
    the analysis process. Motivated by this, the paper presents an approach for the
    automated analysis of geometrical characteristics using clinching as an example.
    @eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: C.
      foaf_name: Zirngibl, C.
      foaf_surname: Zirngibl
  - foaf_Person:
      foaf_givenName: B.
      foaf_name: Schleich, B.
      foaf_surname: Schleich
  bibo_doi: 10.4028/www.scientific.net/KEM.883.105
  bibo_volume: 883 KEM
  dct_date: 2021^xs_gYear
  dct_language: eng
  dct_title: Approach for the automated analysis of geometrical clinch joint characteristics@
...