Projekt | AnDruDok

Publikationen zum Projekt

1. Anomaly Detection in Large Datasets

   Markus Goldstein

   PhD-Thesis, Technische Universität Kaiserslautern, ISBN 978-3-8439-1572-4, Dr. Hut, München, 2/2014.
2. Enhancing One-class Support Vector Machines for Unsupervised Anomaly Detection

   Mennatallah Amer; Markus Goldstein; Slim Abdennadher

   In: Proceedings of the ACM SIGKDD Workshop on Outlier Detection and Description (ODD). International Conference on Knowledge Discovery and Data Mining (KDD-2013), August 11-14, Chicago, IL, USA, Pages 8-15, ISBN 978-1-4503-2335-2, ACM, New York, NY, USA, 8/2013.
3. Document Authentication using Printing Technique Features and Unsupervised Anomaly Detection

   Johann Gebhardt; Markus Goldstein; Faisal Shafait; Andreas Dengel

   In: Proceedings of the 12th International Conference on Document Analysis and Recognition. International Conference on Document Analysis and Recognition (ICDAR-2013), 12th, August 25-28, Washington, DC, USA, Pages 479-483, ISBN 978-0-7695-4999-3, IEEE Computer Society, 8/2013.