Niklas Penzel, M.Sc.
Niklas Penzel
Address: Computer Vision Group
Department of Mathematics and Computer Science
Friedrich Schiller University of Jena
Ernst-Abbe-Platz 2
07743 Jena
Germany
Phone: +49 (0) 3641 9 46335
E-mail: niklas (dot) penzel (at) uni-jena (dot) de
Room: 1224
Links:
Curriculum Vitae
Since Dec. 2020 Research Associate at the Computer Vision Group, Friedrich Schiller University Jena
2020 Master Thesis: “The Bias Uncertainty Sampling introduced into an Active Learning System”
2018-2020 M.Sc. in Computer Science at the Friedrich Schiller University Jena
2018 Bachelor Thesis: “Lebenslanges Lernen von Klassifikationssystemen ohne Vorwissen und mit intelligenter Datenhaltung”
(Lifelong Learning of Classification Systems without Previous Knowledge and with Smart Data Management)
2015-2018 B.Sc. in Computer Science at the Friedrich Schiller University Jena
Research Interests
  • Active Learning
  • Lifelong Learning
  • Deep Learning
  • Super Resolution
Publications
2022
Investigating Neural Network Training on a Feature Level using Conditional Independence
Niklas Penzel and Christian Reimers and Paul Bodesheim and Joachim Denzler.
ECCV Workshop on Causality in Vision (ECCV-WS). 2022. (accepted)
[bibtex] [abstract]
2021
Conditional Dependence Tests Reveal the Usage of ABCD Rule Features and Bias Variables in Automatic Skin Lesion Classification
Christian Reimers and Niklas Penzel and Paul Bodesheim and Jakob Runge and Joachim Denzler.
CVPR ISIC Skin Image Analysis Workshop (CVPR-WS). Pages 1810-1819. 2021.
[bibtex] [pdf] [web] [abstract]
Investigating the Consistency of Uncertainty Sampling in Deep Active Learning
Niklas Penzel and Christian Reimers and Clemens-Alexander Brust and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 159-173. 2021.
[bibtex] [pdf] [web] [abstract]