Matthias Körschens

Institute of Ecology and Evolution | Professorship of Biodiversity of Plants

Kleinwalsertal

Image: Christine Römermann

Institute of Ecology and Evolution | Professorship of Biodiversity of Plants

Matthias Körschens

PhD student

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Image: Matthias Körschens

Otto-Renner-Villa, Room 105
Philosophenweg 16
07743 Jena Google Maps site planExternal link

Research interests

Deep learning
Finegrained Classification & Detection
Unified Networks
Self-Supervised Learning
Weakly Supervised Learning

Curriculum vitae
Since April 2019	PhD Student & research associate at the group Profesorship of Biodiversity of Plants of the FSU Jena
08/2018 – 03/2019	Scientific Assistant at the Computer Vision Group of the FSU Jena
05/2018	Master Thesis with title: "Identification in Wildlife Monitoring"
04/2016 – 05/2018	Master Student in Computer Science at the Friedrich Schiller University Jena
02/2016	Bachelor Thesis with title "Simulation eines kapazitiven Sensors zur Geometriebestimmung und -bewertung eines Katheters"
09/2012 – 02/2016	Bachelor Student in Computer Science at Hochschule Harz in Wernigerode
07/2012	Abitur at the Domgymnasium Merseburg

Publications

Bodesheim, P., Blunk, J., Körschens, M., Brust, C. A., Käding, C., & Denzler, J. (2022). 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, 853–875.
Körschens, M., Bodesheim, P., & Denzler, J. (2022). Beyond Global Average Pooling: Alternative Feature Aggregations for Weakly Supervised Localization. Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, 180-191. DOI: 10.5220/0010871700003124.
Körschens, M., Bodesheim, P., & Denzler, J. (2022). Occlusion-Robustness of Convolutional Neural Networks via Inverted Cutout. In 2022 26th International Conference on Pattern Recognition (ICPR) (pp. 2829-2835). IEEE.
Gruner, B., Körschens, M., Barz, B., & Denzler, J. (2021). Domain Adaptation and Active Learning for Fine-Grained Recognition in the Field of Biodiversity. arXiv preprint arXiv:2110.11778.
Körschens, M., Bodesheim, P., Römermann, C., Bucher, S.F., Migliavacca, M., Ulrich, J., Denzler, J. (2021) Weakly Supervised Segmentation Pretraining for Plant Cover Prediction. In: Bauckhage C., Gall J., Schwing A. (eds) Pattern Recognition. DAGM GCPR 2021. Lecture Notes in Computer Science, vol 13024. Springer, Cham. https://doi.org/10.1007/978-3-030-92659-5_38External link
Körschens, M., Bodesheim, P., Römermann, C., Bucher, S.F., Migliavacca, M., Ulrich, J., Denzler, J. (2021) Automatic Plant Cover Estimation with Convolutional Neural Networks, CS4BioDiversity Workshop der INFORMATIK2021
Körschens, M., Bodesheim, P., Römermann, C., Bucher, S.F., Ulrich, J., Denzler, J. (2020) Towards Confirmable Automated Plant Cover Determination. In: Bartoli A., Fusiello A. (eds) Computer Vision – ECCV 2020 Workshops. ECCV 2020. Lecture Notes in Computer Science, vol 12540. Springer, Cham. https://doi.org/10.1007/978-3-030-65414-6_22External link
Körschens, M., Denzler, J. (2019) ELPephants: A Fine-Grained Dataset for Elephant Re-Identification. The IEEE International Conference on Computer Vision (ICCV) Workshop
Körschens, M., Barz, B., Denzler J. (2018) Towards Automatic Identification of Elephants in the Wild, AI for Wildlife Conservation Workshop (AIWC).

Conference contributions

Körschens, M., Römermann, C., Bucher, S. F., Ulrich, J., Denzler, J. (2019) Deep Learning Approaches for Automatic Analysis of Plant Species and Cover Determination. iDiv-Konferenz Leipzig & GfÖ Jahrestagung Münster, Poster
Körschens M., Barz B., Denzler, J. (2018) Towards Automatic Identification of Elephants in the Wild. ICEI 2018, Jena, Poster