---
res:
  bibo_abstract:
  - The production of printing goods is laborious. Furthermore, the print quality,
    especially in banknotes, must be assured. It is accepted, that print defects are
    generated because printing parameters, also machine parameters can change unnoticed.
    Therefore, a combined concept for a multi-sensory learning and classification
    model based on new adaptive fuzzy-pattern-classifiers for data inspection is proposed.
    This inspection concept, which combines optical, acoustical and other machine
    information, comes up with a large amount of data, which leads to multivariate
    methods for data analysis. Multivariate methods are useful for analysis of large
    and complex data sets that consist of many variables measured on large numbers
    of physical data.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Walter
      foaf_name: Dyck, Walter
      foaf_surname: Dyck
  - foaf_Person:
      foaf_givenName: Thomas
      foaf_name: Türke, Thomas
      foaf_surname: Türke
  - foaf_Person:
      foaf_givenName: Johannes
      foaf_name: Schaede, Johannes
      foaf_surname: Schaede
      foaf_workInfoHomepage: http://www.librecat.org/personId=2128
  - foaf_Person:
      foaf_givenName: Volker
      foaf_name: Lohweg, Volker
      foaf_surname: Lohweg
      foaf_workInfoHomepage: http://www.librecat.org/personId=1804
    orcid: 0000-0002-3325-7887
  bibo_doi: 10.1109/MLSP.2007.4414320
  dct_date: 2007^xs_gYear
  dct_isPartOf:
  - 'http://id.crossref.org/issn/1551-2541 '
  - http://id.crossref.org/issn/978-1-4244-1565-6
  dct_language: eng
  dct_publisher: MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL
    PROCESSING@
  dct_subject:
  - Sensor fusion
  - Inspection
  - Optical sensors
  - Printing machinery
  - Data security
  - Data analysis
  - Production
  - Degradation
  - Principal component analysis
  - Karhunen-Loeve transforms
  dct_title: A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion@
...