Kleinwalsertal

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
vCard
Matthias Körschens
Image: Matthias Körschens
Inspektorhaus, Room D 103
Fürstengraben 26
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
    • Körschens, M., Bucher, S. F., Bodesheim, P., Ulrich, J., Denzler, J., & Römermann, C. (2024). Determining the community composition of herbaceous species from images using convolutional neural networks. Ecological Informatics, 80, 102516.
    • Körschens, M., Bucher, S. F., Römermann, C., & Denzler, J. (2023). Unified Automatic Plant Cover and Phenology Prediction. In Proceedings of the IEEE/CVF International Conference on Computer Vision (pp. 685-693).
    • Körschens, M., Bucher, S. F., Römermann, C., & Denzler, J. (2023, September). Improving Data Efficiency for Plant Cover Prediction with Label Interpolation and Monte-Carlo Cropping. In DAGM German Conference on Pattern Recognition (pp. 321-334). Cham: Springer Nature Switzerland.
    • 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
    • Matthias Körschens, Solveig Franziska Bucher, Paul Bodesheim, Joachim Denzler, Harald Auge, Jes Hines, Christine Römermann (2025) "PlantCAPNet: Automatic Extraction of Plant Species Abundances and Phenology from Images from the GCEF and Beyond". "10 years of GCEF" Workshop Halle (Saale).
    • Matthias Körschens, Solveig Franziska Bucher, Paul Bodesheim, Joachim Denzler, Harald Auge, Jes Hines, Christine Römermann (2024) "PlantCAPNet: Automatic Extraction of Plant Species Abundances and Phenology from Images". iDiv-Konferenz Leipzig.
    • Matthias Körschens, Solveig Franziska Bucher, Christine Römermann, Joachim Denzler. (2023). “Unified Automatic Plant Cover and Phenology Prediction”. CVPPA Workshop of the ICCV 2023.
    • Matthias Körschens, Solveig Franziska Bucher, Christine Römermann, Joachim Denzler. (2023). “Improving Data Efficiency for Plant Cover Prediction with Label Interpolation and Monte-Carlo Cropping”. GCPR 2023.
    • Matthias Körschens, Solveig Franziska Bucher, Joachim Denzler, Christine Römermann (2023) "Combined Extraction of Plant Species Abundances and Plant Phenology from Images using Convolutional Neural Networks". GfÖ Jahrestagung Leipzig.
    • Matthias Körschens, Paul Bodesheim, Joachim Denzler. (2022). “Occlusion-Robustness of Convolutional Neural Networks via Inverted Cutout”. ICPR 2022
    • Matthias Körschens, Solveig Franziska Bucher, Paul Bodesheim, Joachim Denzler, Josephine Ulrich, Christine Römermann (2022) "Extracting Information on Plant Species Abundances from Images using Convolutional Neural Networks". GfÖ Jahrestagung Metz.
    • Matthias Körschens, Paul Bodesheim, Joachim Denzler (2022). “Beyond Global Average Pooling: Alternative Feature Aggregations for Weakly Supervised Localization”. VISAPP 2022 (Online).
    • Matthias Körschens, Solveig Franziska Bucher, Paul Bodesheim, Joachim Denzler, Josephine Ulrich, Christine Römermann (2021) "Automated Plant Cover Prediction with Convolutional Neural Networks". GfÖ Jahrestagung (Online).
    • Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Mirco Migliavacca, Josephine Ulrich, Joachim Denzler. (2021). “Automatic Plant Cover Estimation with Convolutional Neural Networks”. GI-Jahrestagung (Online).
    • Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Mirco Migliavacca, Josephine Ulrich, Joachim Denzler. (2021). “Weakly Supervised Segmentation Pretraining for Plant Cover Prediction”. GCPR 2021 (Online).
    •  Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Josephine Ulrich, Joachim Denzler. (2020). Towards confirmable automated plant cover determination. ECCV 2020 (Online).
    • Matthias Körschens, Paul Bodesheim, Joachim Denzler. (2019). “Elpephants: A fine-grained dataset for elephant re-identification”. CVWC Workshop of the ICCV 2019.
    • 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.
    • Matthias Körschens, Björn Barz, Joachim Denzler (2018). “Towards automatic identification of elephants in the wild”. IJCAI Workshop: AI for Wildlife Conservation Workshop (AIWC), Stockholm.
    • Körschens M., Barz B., Denzler, J. (2018) Towards Automatic Identification of Elephants in the Wild. ICEI 2018, Jena, Poster.