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Dr. Nicolas Cebron

From Multimedia Computing Lab - University of Augsburg


Main

Former Staff Member

My current webpage can be found here.

Research Interests

  • Machine Learning
  • Active Learning
  • Computer Vision
  • Image Processing

Projects

Teaching


Publications

Journals

  • Fabian Richter, Christian X. Ries, Nicolas Cebron, Rainer Lienhart. Learning to Reassemble Shredded Documents, IEEE Transactions on Multimedia, 2012 (to appear)
  • Nicolas Cebron. Active Improvement of Hierarchical Object Features under Budget Constraints, Frontiers of Computer Science, Springer, April 2012 (in press).
  • Nicolas Cebron and Michael R. Berthold. Active Object Classification: From Exploration to Exploitation, Journal of Data Mining and Knowledge Discovery,vol. 18, no. 2, pp. 283-299, Springer, 2009. DOI:10.1007/s10618-008-0115-0
  • Michael R. Berthold, Nicolas Cebron, Fabian Dill, Thomas Gabriel,Tobias Kötter, Thorsten Meinl, Peter Ohl,Kilian Thiel, and Bernd Wiswedel. KNIME - the Konstanz information miner: version 2.0 and beyond, SIGKDD Explor. Newsl.,vol. 11, no. 1, pp. 26- 31, 2009. DOI:10.1145/1656274.1656280
  • Nicolas Cebron and Michael R. Berthold. Adaptive Prototype Based Fuzzy Classification, Fuzzy Sets and Systems, vol. 159, no. 21, pp. 2806-2818 , Elsevier B.V., 2008. DOI:10.1016/j.fss.2008.03.019

Conference Papers and Workshop Papers

  • Nicolas Cebron, Fabian Richter and Rainer Lienhart. Decision Tree Induction from Counterexamples, International Conference on Pattern Recognition Applications and Methods (ICPRAM), February 2012, Vilamoura, Portugal.
  • Nicolas Cebron. Active Improvement of Hierarchical Object Features under Budget Constraints, 10th IEEE International Conference on Data Mining (ICDM), December 2010, Sydney, Australia. DOI:10.1109/ICDM.2010.74
  • Nicolas Cebron and Michael R. Berthold. Active Learning in Parallel Universes, 19th ACM International Conference on Information and Knowledge Management (CIKM), October 2010, Toronto, Canada. DOI:10.1145/1871437.1871688
  • Nicolas Cebron. Towards Learning with Objects in a Hierarchical Representation, International Conference on Knowledge Discovery and Information Retrieval (KDIR), October 2010, Valencia, Spain. DOI:10.5220/0003114403260329
  • Thomas Gloe, Nicolas Cebron, and Rainer Böhme. An ML Perspective on Feature-Based Forensic Camera Model Identification, Workshop: Pattern Recognition for IT Security, Symposium of the German Association for Pattern Recognition (DAGM), September 2010, Darmstadt, Germany.
  • Nicolas Cebron. Cell Assay Image Classification with Few Labeled Examples, The 2010 International Conference on Bioinformatics & Computational Biology (BIOCOMP), July 2010, Las Vegas, USA.
  • Nicolas Cebron. Adaption of Observations under Budget Constraints in Active Learning, Workshop: Towards Closing the Loop: Active Learning for Robotics, Robotics: Science and Systems (RSS 2010), June 2010, Zaragoza, Spain.
  • Michael R. Berthold, Nicolas Cebron, Fabian Dill, Thomas Gabriel, Tobias Koetter, Thorsten Meinl, Peter Ohl, Christoph Sieb, Kilian Thiel, Bernd Wiswedel. The Konstanz Information Miner 2.0, Workshop Open Source in Data Mining, Pacific-Asia Knowledge Discovery and Data Mining conference (PAKDD), pp. 26-31, Bangkok, Thailand, 2009.
  • Michael R. Berthold, Nicolas Cebron, Fabian Dill, Thomas Gabriel, Tobias Koetter, Thorsten Meinl, Peter Ohl, Christoph Sieb, Kilian Thiel, Bernd Wiswedel. Knime: The Konstanz Information Miner, Proceedings Studies in Classification, Data Analysis, and Knowledge Organization (GfKL), Freiburg, Germany, Springer-Verlag, 2007.
  • Nicolas Cebron und Michael R. Berthold. Adaptive Active Classification of Cell Assay Images, European Conference on Principles and Practice of Knowledge Discovery (PKDD), LNCS, vol. 4213, pp. 79-90, Springer Berlin / Heidelberg, 2006. DOI:10.1007/11871637_12
  • Nicolas Cebron und Michael R. Berthold. Adaptive Fuzzy Clustering, Proceedings Conf. North American Fuzzy Information Processing Society (NAFIPS), pp. 188-193, Montreal, Canada, 2006. DOI:10.1109/NAFIPS.2006.365406
  • Nicolas Cebron und Michael R. Berthold. Adaptive Klassifikation von Zellbildern, Proceedings 16. Workshop Computational Intelligence, pp. 223-234, Dortmund, Germany, 2006.
  • Nicolas Cebron und Michael R. Berthold. Mining of Cell Assay Images using Active Semisupervised Clustering, Proceedings Workshop Computational Intelligence in Data Mining, IEEE International Conference on Data Mining (ICDM), pp. 63-69, Houston, USA, 2005.

Presentations

  • Nicolas Cebron, Fabian Richter and Rainer Lienhart. Towards Learning with Complementary Labels, International Classification Conference (ICC), July 2011, St. Andrews, Scotland.

Technical Reports

  • Nicolas Cebron, Michael R. Berthold. An adaptive multi objective selection strategy for active learning, Konstanzer Schriften in Mathematik und Informatik, No. 235, University of Konstanz, August 2007.

Theses

  • Nicolas Cebron: Active Learning for Classification of Large Datasets using Exploration and Exploitation, University of Konstanz, May 2008. PDF