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Dr.-Ing. Paul Bodesheim

Team Leader: "Computer Vision and Machine Learning"
bodesheim.jpg
 

Contact

Address:






Computer Vision Group
Institute for Computer Science
Department of Mathematics and Computer Science
Friedrich Schiller University Jena
Ernst-Abbe-Platz 2
07743 Jena
Germany
Room: 1218
Phone: +49 (0) 3641 9 46410
E-Mail: paul.bodesheim (at) uni-jena.de

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Curriculum Vitæ

 since Jun 2020
  Team Leader: "Computer Vision and Machine Learning"
Computer Vision Group, Friedrich Schiller University Jena
 Oct 2018 to May 2020
  Research Associate / Postdoc
Computer Vision Group, Friedrich Schiller University Jena
 Jan 2015 to Sep 2018
  Research Associate / Postdoc
Department Biogeochemical Integration, Max Planck Institute for Biogeochemistry
 Apr 2011 to Dec 2014
  Research Associate / PhD Student
Computer Vision Group, Friedrich Schiller University Jena
PhD Thesis: "Discovering unknown visual objects with novelty detection techniques"
 Oct 2006 to Mar 2011
  Studies in Computer Science (Diploma)
Friedrich Schiller University Jena
Focus: Digitial Image Processing / Computer Vision
Diploma Thesis: "Object Discovery - Unsupervised Learning of Object Categories"

Awards

  • Best Paper Award at Anomaly Detection Workshop of ICML 2016 (Rodner, Barz, Guanche, Flach, Mahecha, Bodesheim, Reichstein, Denzler: "Maximally Divergent Intervals for Anomaly Detection")
  • Best Poster Award at FEAST Workshop of ICPR 2014 (Freytag, Rühle, Bodesheim, Rodner, Denzler: "Seeing through bag-of-visual-word glasses: towards understanding quantization effects in feature extraction methods")
  • Best Paper Honorable Mention Award at ACCV 2012 (Freytag, Rodner, Bodesheim, Denzler: "Rapid Uncertainty Computation with Gaussian Processes and Histogram Intersection Kernels")

List of Publications

Research Interests

  • Visual Object Recognition
  • Learning from Small and Imbalanced Data
  • Fine-grained Recognition and Applications in Biodiversity Research
  • Novelty Detection and Open Set Recognition
  • Active Learning and Lifelong Learning

Projects (Third-Party Funds)

Ongoing

Former

Projects (Further)

Ongoing

Former

Reviewer Activities

Winter Terms

  • "Maschinelles Lernen und Datamining" / Machine Learning and Data Mining
    • Lecture (4 SWS): 2021/2022
  • "Informatik (B.Sc. Werkstoffwissenschaften)" / Computer Science for Materials Scientists
    • Lecture (3 SWS): 2021/2022, 2020/2021, 2019/2020, 2018/2019
    • Exercise (3 SWS): 2018/2019
  • "Informatik II (B.Sc. Physik)" / Computer Science II for Physicists
    • Lecture (2 SWS): 2021/2022, 2020/2021, 2019/2020, 2018/2019
    • Exercise (1 SWS): 2019/2020, 2018/2019

Summer Terms

  • "Visuelle Objekterkennung" / Visual Object Recognition
    • Lecture (2 SWS): 2021, 2020, 2019
  • "Informatik I (B.Sc. Physik)" / Computer Science I for Physicists
    • Lecture (2 SWS): 2021, 2020, 2019
    • Exercise (1 SWS): 2020, 2019

Supervised Theses

  • Jan Blunk: "Object Tracking in Wildlife Identification". Bachelor Thesis, 2021. (joint supervision with Matthias Körschens)
  • Daphne Auer: "Applying Wavelet Transforms prior to Convolutional Neural Networks for Image Categorization". Bachelor Thesis, 2020.
  • Hendrik Happe: "Aktivierungsfunktionen in neuronalen Netzen für die visuelle Objekterkennung" ("Activation Functions in Neural Networks for Visual Object Recognition"). Master Thesis, 2020. (joint supervision with Christian Reimers)
  • Frank Prüfer: "Detektion von unbekannten Objekten durch Entscheidungswälder und Gauß-Prozesse" ("Detecting Unknown Objects with Decision Forests and Gaussian Processes"). Diploma Thesis, 2013.
  • Sven Sickert: "Strategien des Aktiven Lernens" ("Strategies in Active Learning"). Diploma Thesis, 2012. (joint supervision with Alexander Freytag)