---
res:
  bibo_abstract:
  - During the industrial processing of materials for the manufacture of new products,
    surface defects can quickly occur. In order to achieve high quality without a
    long time delay, it makes sense to inspect the work pieces so that defective work
    pieces can be sorted out right at the beginning of the process. At the same time,
    the evaluation unit should come close the perception of the human eye regarding
    detection of defects in surfaces. Such defects often manifest themselves by a
    deviation of the existing structure. The only restriction should be that only
    matt surfaces should be considered here. Therefore in this work, different classification
    and image processing algorithms are applied to surface data to identify possible
    surface damages. For this purpose, the Gabor filter and the FST (Fused Structure
    and Texture) features generated with it, as well as the salience metric are used
    on the image processing side. On the classification side, however, deep neural
    networks, Convolutional Neural Networks (CNN), and autoencoders are used to make
    a decision. A distinction is also made between training using class labels and
    without. It turns out later that the salience metric are best performed by CNN.
    On the other hand, if there is no labeled training data available, a novelty classification
    can easily be achieved by using autoencoders as well as the salience metric and
    some filters.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Tom
      foaf_name: Sander, Tom
      foaf_surname: Sander
  - foaf_Person:
      foaf_givenName: Sven
      foaf_name: Lange, Sven
      foaf_surname: Lange
      foaf_workInfoHomepage: http://www.librecat.org/personId=38240
  - foaf_Person:
      foaf_givenName: Ulrich
      foaf_name: Hilleringmann, Ulrich
      foaf_surname: Hilleringmann
  - foaf_Person:
      foaf_givenName: Volker
      foaf_name: Geneis, Volker
      foaf_surname: Geneis
  - foaf_Person:
      foaf_givenName: Christian
      foaf_name: Hedayat, Christian
      foaf_surname: Hedayat
  - foaf_Person:
      foaf_givenName: Harald
      foaf_name: Kuhn, Harald
      foaf_surname: Kuhn
  - foaf_Person:
      foaf_givenName: Franz-Barthold
      foaf_name: Gockel, Franz-Barthold
      foaf_surname: Gockel
  bibo_doi: 10.1109/icit46573.2021.9453646
  dct_date: 2021^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/9781728157306
  dct_language: eng
  dct_publisher: IEEE@
  dct_subject:
  - Image Processing
  - Defect Detection
  - wooden surfaces
  - Machine Learning
  - Neural Networks
  dct_title: Detection of Defects on Irregular Structured Surfaces by Image Processing
    Methods for Feature Extraction@
...