@inproceedings{2070,
  abstract     = {{A Two-Layer Conflict Solving data fusion approach is proposed in this work, with an aim to provide another approach to data fusion community. Since the evidence of Dempster-Shafer Theory, algorithms for combining pieces of evidence have drawn a considerable attention from data fusion researchers, along with many alternatives invented. However, none of these approaches receive an agreement for being able to perform very successfully in all scenarios and hence this topic is still in hot discussion. Therefore, the suggested approach in this work will contribute as a novel method and present its own merits. }},
  author       = {{Li, Rui and Lohweg, Volker}},
  keywords     = {{fusion community, data fusion researcher, dempster-shafer theory, many alternative, novel method, considerable attention, hot discussion, suggested approach}},
  title        = {{{A Novel Data Fusion Approach using Two-Layer Conflict Solving}}},
  year         = {{2008}},
}

@inproceedings{2071,
  abstract     = {{In this paper, a fuzzy pattern classification tuning approach is proposed, which is based on fusion concept. In this method, tuning parameters are learned in a training procedure, enabling system to be capable of managing individual classification task. Fuzzy c-means, as a specific instance of Tuning Reference, is employed as a tool to offer membership function which is used for making decisions and its membership function fuses (tunes) another membership function captured from fuzzy pattern classification and then final decisions are made upon fused one. Experiments are taken on five benchmark datasets, one of them shows an equal performance and the other four present better results than each single classifier.}},
  author       = {{Li, Rui and Lohweg, Volker}},
  isbn         = {{978-3-8007-3092-6}},
  keywords     = {{tuning parameter, information fusion, fuzzy cmeans, membership function, fuzzy pattern classification}},
  publisher    = {{In: The 11th Conference on Information Fusion, June 30 - July 3, Cologne, Germany}},
  title        = {{{Fuzzy Pattern Classification Tuning by Parameter Learning based on Fusion Concept}}},
  year         = {{2008}},
}

@inproceedings{2072,
  author       = {{Lohweg, Volker and Possel-Dölken, Frank}},
  publisher    = {{Innovationsdialog NRW, dSPACE GmbH, Technologiepark, Paderborn}},
  title        = {{{Oberflächenanalyse mit intelligenten Netzwerk-Kameras - Virtuelle Produktentwicklung mit Simulation/Verkürzung Time-to-Market durch Einsatz von Simulationstechniken}}},
  year         = {{2008}},
}

@inproceedings{2073,
  abstract     = {{Synthetic surfaces, in particular polymer structures, which are used for electronic components, have to be inspected in industrial processes. Polymers show some specific surface characteristics. This a-priori knowledge is useable for the feature extraction of a surface texture and a following classification. The feature extraction is performed by using statistical information, calculated from sum and difference histograms, while the classification is executed by a fuzzy pattern classifier. A defect area can be recognized just on the basis of the tested image and without the need of any further reference learning data. The classification of a defect part is achieved by analyzing the divergence of the extracted feature values from their median related to the inspected area. Surfaces that contain an inconsistent texture will be rejected.}},
  author       = {{Niederhöfer, Marcus and Lohweg, Volker}},
  booktitle    = {{13th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2008)}},
  title        = {{{Application-based Approach for Automatic Texture Defect Recognition on Synthetic Surfaces}}},
  doi          = {{10.1109/ETFA.2008.4638397}},
  year         = {{2008}},
}

@inproceedings{2074,
  abstract     = {{Veranstaltungsreihe quot;solution OWLquot;; }},
  author       = {{Lohweg, Volker}},
  publisher    = {{Veranstaltungsreihe "solution OWL", Claas Technoparc, Harsewinkel, 28.10.2008}},
  title        = {{{Intelligente Automation durch Sensorfusion, Adaptronik - Mediatronik - Kognitronik – Schlüssel für die Entwicklung intelligenter Systeme}}},
  year         = {{2008}},
}