Dr. rer. nat. Clemens-Alexander Brust
Curriculum Vitae
  • 2017-2021: Research Associate with the Computer Vision Group at Friedrich Schiller University Jena
  • 2017: Master Thesis “Incremental Learning of YOLO Object Detection”
  • 2015-2017: Studies of Computational and Data Science at Friedrich Schiller University Jena
  • 2014: Bachelor Thesis “Convolutional Networks for Automatic Road Segmentation”
  • 2010-2014: Studies of Computer Science at Friedrich Schiller University Jena
Research Interests
  • Hierarchical Classification
  • Lifelong Learning
  • Learning with Few Examples
Publications
2022
Paul Bodesheim, Jan Blunk, Matthias Körschens, Clemens-Alexander Brust, Christoph Käding, Joachim Denzler:
Pre-trained models are not enough: active and lifelong learning is important for long-term visual monitoring of mammals in biodiversity research. Individual identification and attribute prediction with image features from deep neural networks and decoupled decision models applied to elephants and great apes.
Mammalian Biology. 102 : pp. 875-897. 2022.
[bibtex] [web] [doi] [abstract]
2021
Clemens-Alexander Brust, Björn Barz, Joachim Denzler:
Carpe Diem: A Lifelong Learning Tool for Automated Wildlife Surveillance.
Computer Science for Biodiversity Workshop (CS4Biodiversity), INFORMATIK 2021. Pages 417-423. 2021.
[bibtex] [pdf] [doi]
Clemens-Alexander Brust, Björn Barz, Joachim Denzler:
Self-Supervised Learning from Semantically Imprecise Data.
arXiv preprint arXiv:2104.10901. 2021.
[bibtex] [pdf] [abstract]
Niklas Penzel, Christian Reimers, Clemens-Alexander Brust, Joachim Denzler:
Investigating the Consistency of Uncertainty Sampling in Deep Active Learning.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 159-173. 2021.
[bibtex] [pdf] [web] [doi] [abstract]
2020
Clemens-Alexander Brust, Björn Barz, Joachim Denzler:
Making Every Label Count: Handling Semantic Imprecision by Integrating Domain Knowledge.
International Conference on Pattern Recognition (ICPR). 2020.
[bibtex] [pdf] [doi] [abstract]
Clemens-Alexander Brust, Christoph Käding, Joachim Denzler:
Active and Incremental Learning with Weak Supervision.
Künstliche Intelligenz (KI). 2020.
[bibtex] [pdf] [doi] [abstract]
2019
Clemens-Alexander Brust, Christoph Käding, Joachim Denzler:
Active Learning for Deep Object Detection.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 181-190. 2019.
[bibtex] [pdf] [doi] [abstract]
Clemens-Alexander Brust, Joachim Denzler:
Integrating Domain Knowledge: Using Hierarchies to Improve Deep Classifiers.
Asian Conference on Pattern Recognition (ACPR). 2019.
[bibtex] [pdf] [abstract]
Clemens-Alexander Brust, Joachim Denzler:
Not just a Matter of Semantics: The Relationship between Visual Similarity and Semantic Similarity.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 414-427. 2019.
[bibtex] [pdf] [doi] [abstract]
Marie Arlt, Jack Peter, Sven Sickert, Clemens-Alexander Brust, Joachim Denzler, Andreas Stallmach:
Automated Polyp Differentiation on Coloscopic Data using Semantic Segmentation with CNNs.
Endoscopy. 51 (04) : pp. 4. 2019.
[bibtex] [web] [doi] [abstract]
Stefan Hoffmann, Clemens-Alexander Brust, Maha Shadaydeh, Joachim Denzler:
Registration of High Resolution Sar and Optical Satellite Imagery Using Fully Convolutional Networks.
International Geoscience and Remote Sensing Symposium (IGARSS). Pages 5152-5155. 2019.
[bibtex] [pdf] [doi] [abstract]
2018
Christoph Theiß, Clemens-Alexander Brust, Joachim Denzler:
Dataless Black-Box Model Comparison.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 28 (4) : pp. 676-683. 2018. (also published at ICPRAI 2018)
[bibtex] [doi] [abstract]
Joachim Denzler, Christoph Käding, Clemens-Alexander Brust:
Keeping the Human in the Loop: Towards Automatic Visual Monitoring in Biodiversity Research.
International Conference on Ecological Informatics (ICEI). Pages 16. 2018.
[bibtex] [doi] [abstract]
2017
Clemens-Alexander Brust, Christoph Käding, Joachim Denzler:
You Have To Look More Than Once: Active and Continuous Exploration using YOLO.
CVPR Workshop on Continuous and Open-Set Learning (CVPR-WS). 2017. Poster presentation and extended abstract
[bibtex] [abstract]
Clemens-Alexander Brust, Tilo Burghardt, Milou Groenenberg, Christoph Käding, Hjalmar Kühl, Marie Manguette, Joachim Denzler:
Towards Automated Visual Monitoring of Individual Gorillas in the Wild.
ICCV Workshop on Visual Wildlife Monitoring (ICCV-WS). Pages 2820-2830. 2017.
[bibtex] [pdf] [doi] [abstract]
2016
Clemens-Alexander Brust, Sven Sickert, Marcel Simon, Erik Rodner, Joachim Denzler:
Neither Quick Nor Proper -- Evaluation of QuickProp for Learning Deep Neural Networks.
2016. Technical Report TR-FSU-INF-CV-2016-01
[bibtex] [pdf] [abstract]
2015
Clemens-Alexander Brust, Sven Sickert, Marcel Simon, Erik Rodner, Joachim Denzler:
Convolutional Patch Networks with Spatial Prior for Road Detection and Urban Scene Understanding.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 510-517. 2015.
[bibtex] [pdf] [doi] [abstract]
Clemens-Alexander Brust, Sven Sickert, Marcel Simon, Erik Rodner, Joachim Denzler:
Efficient Convolutional Patch Networks for Scene Understanding.
CVPR Workshop on Scene Understanding (CVPR-WS). 2015. Poster presentation and extended abstract
[bibtex] [pdf] [abstract]