• Karbstein, K., Kösters, L., Hodač, L., Hofmann, M., Hörandl, E., Tomasello, S., Wagner, N., Emerson, B., Albach, D., Scheu, S., Bradler, S., de Vries, J., Irisarri, I., Li, H., Soltis, P., Mäder, P., Wäldchen, J. (2024) Species delimitation 4.0: integrative taxonomy meets artificial intelligence. Trends in Ecology & Evolution. https://doi.org/10.1016/j.tree.2023.11.002
  • Rzanny, M., Mäder, P., Wittich, H.C., Boho, D. & Wäldchen, J. (2024) Opportunistic plant observations reveal spatial and temporal gradients in phenology. npj biodivers 3, 5. https://doi.org/10.1038/s44185-024-00037-7
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  • Bebber, A., Wäldchen, J., Rzanny, M., Boho, D., Wittich, HC, Fritz, A. & Mäder, P. (2023). Flora Incognita – Automatisierte Pflanzenbestimmung ermöglicht bürgerwissenschaftliches Pflanzenmonitoring. – Landschaftspflege und Naturschutz in Thüringen 59 (4): 180-183
  • Katal, N. & Rzanny, M., Mäder, P., Römermann, C., Wittich, H. C., Boho, D., Musavi, T. & Wäldchen, J. (2023). Bridging the gap: how to adopt opportunistic plant observations for phenology monitoring. Front. Plant Sci. 14:1150956  https://doi.org/10.3389/fpls.2023.1150956 
  • Hodač, L., Karbstein, K., Tomasello, S., Wäldchen, J., Bradican, J. P., & Hörandl, E. (2023). Geometric morphometric versus genomic patterns in a large polyploid plant species complex. Biology, 12(3), 418.
  • Milz, S., Wäldchen, J., Abouee, A. et al. The HAInich: A multidisciplinary vision data-set for a better understanding of the forest ecosystem. Sci Data 10, 168 (2023). https://doi.org/10.1038/s41597-023-02010-8


  • Wäldchen, J., Wittich, H. C., Rzanny, M., Fritz, A., & Mäder, P. (2022). Towards more effective identification keys: A study of people identifying plant species characters. People and Nature. https://doi.org/10.1002/pan3.10405
  • van Klink, R., August, T., Bas, Y., Bodesheim, P., Bonn, A., Fossøy, F., … Wäldchen, J. & Bowler, D. E. (2022). Emerging technologies revolutionise insect ecology and monitoring. Trends in Ecology & Evolution.
  • Katal, N., Rzanny, M., Mäder, P., & Wäldchen, J. (2022). Deep learning in plant phenological research: A systematic literature review. Frontiers in Plant Science, 13. https://doi.org/10.3389/fpls.2022.805738
  • Rzanny M, Wittich HC, Mäder P, Deggelmann A, Boho D & Wäldchen J (2022) Image-Based Automated Recognition of 31 Poaceae Species: The Most Relevant Perspectives. Front. Plant Sci. 12:804140. https://doi.org/10.3389/fpls.2021.804140


  • Pärtel, J., Pärtel, M., & Wäldchen, J. (2021). Plant image identification application demonstrates high accuracy in Northern Europe. AoB PLANTS. Volume 13, Issue 4, https://doi.org/10.1093/aobpla/plab050 (Editors’ Choice)
  • Mäder, P., Boho, D., Rzanny, M., Seeland, M., Wittich, H. C., Deggelmann, A., & Wäldchen, J. (2021). The flora incognita app–interactive plant species identification. Methods in Ecology and Evolution. 12: 13351342. https://doi.org/10.1111/2041-210X.13611
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  • Seeland, M. & Mäder, P. (2021). “Multi-view classification with convolutional neural networks.” Plos one 16.1: e0245230.


  • Boho, D., Rzanny, M., Wäldchen, J., Nitsche, F., Deggelmann, A., Wittich, H. C., … & Mäder, P. (2020). Flora Capture: a citizen science application for collecting structured plant observations. BMC bioinformatics, 21(1), 1-11. https://doi.org/10.1186/s12859-020-03920-9


  • Rzanny, M., Mäder, P., Deggelmann, A., Chen, M., & Wäldchen, J. (2019). Flowers, leaves or both? How to obtain suitable images for automated plant identification. Plant methods, 15(1), 77. https://doi.org/10.1186/s13007-019-0462-4
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  • Seeland, M., Rzanny, M., Boho, D., Wäldchen, J.  & Mäder, P. (2019). Image-based classification of plant genus and family for trained and untrained plant species. BMC Bioinformatics 20:4 https://doi.org/10.1186/s12859-018-2474-x
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  • Wittich, H. C., Seeland, M., Wäldchen, J., Rzanny, M. & Mäder, P. (2018). Recommending plant taxa for supporting on-site species identification. BMC Bioinformatics. 19(190). https://doi.org/10.1186/s12859-018-2201-7  
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  • Rzanny, M., Seeland, M., Wäldchen, J., & Mäder, P. (2017). Acquiring and preprocessing leaf images for automated plant identification: understanding the tradeoff between effort and information gain. Plant Methods, 13(1), 97. https://doi.org/10.1186/s13007-017-0245-8
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