Journal Article (37)

21.
Journal Article
Karbstein, K.; Tomasello, S.; Hodac, L.; Wagner, N.; Marinček, P.; Barke, B. H.; Paetzold, C.; Hörandl, E.: Untying Gordian knots: unraveling reticulate polyploid plant evolution by genomic data using the large Ranunculus auricomus species complex. New Phytologist 235 (5), pp. 2081 - 2098 (2022)
22.
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Katal, N.; Rzanny, M.; Mäder, P.; Wäldchen, J.: Deep learning in plant phenological research: A systematic literature review. Frontiers in Plant Science 13, 805738 (2022)
23.
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Schmid, B.; Schmitz, M.; Rzanny, M.; Scherer-Lorenzen, M.; Mwangi, P. N.; Weisser, W. W.; Hector, A.; Schmid, R.; Flynn, D. F. B.: Removing subordinate species in a biodiversity experiment to mimic observational field studies. Grassland Research 1 (1), pp. 53 - 62 (2022)
24.
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Rzanny, M.; Wittich, H. C.; Mäder, P.; Deggelmann, A.; Boho, D.; Wäldchen, J.: Image-based automated recognition of 31 Poaceae species: The most relevant perspectives. Frontiers in Plant Science 12, 804140 (2022)
25.
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Pärtel, J.; Pärtel, M.; Wäldchen, J.: Plant image identification application demonstrates high accuracy in Northern Europe. AOB PLANTS 13 (4), plab050 (2021)
26.
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Mäder, P.; Boho, D.; Rzanny, M.; Seeland, M.; Wittich, H. C.; Deggelmann, A.; Wäldchen, J.: The Flora Incognita app – interactive plant species identfication. Methods in Ecology and Evolution 12 (7), pp. 1335 - 1342 (2021)
27.
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Boho, D.; Rzanny, M.; Wäldchen, J.; Nitsche, F.; Deggelmann, A.; Wittich, H.-C.; Seeland, M.; Mäder, P.: Flora Capture: a citizen science application for collecting structured plant observations. BMC Bioinformatics 21, 576 (2020)
28.
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Rzanny, M.; Mäder, P.; Deggelmann, A.; Chen, M.; Wäldchen, J.: Flowers, leaves or both? How to obtain suitable images for automated plant identification. Plant Methods 15, 77 (2019)
29.
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Seeland, M.; Rzanny, M.; Boho, D.; Wäldchen, J.; Mäder, P.: Image-based classification of plant genus and family for trained and untrained plant species. BMC Bioinformatics 20, 4 (2019)
30.
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Dunker, S.; Boho, D.; Wäldchen, J.; Mäder, P.: Combining high‑throughput imaging flow cytometry and deep learning for efficient species and life‑cycle stage identification of phytoplankton. BMC Ecology 18, 51 (2018)
31.
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Wäldchen, J.; Mäder, P.: Machine learning for image based species identification. Methods in Ecology and Evolution 9 (11), pp. 2216 - 2225 (2018)
32.
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Wittich, H. C.; Seeland, M.; Wäldchen, J.; Rzanny, M.; Mäder, P.: Recommending plant taxa for supporting on-site species identification. BMC Bioinformatics 19, 190 (2018)
33.
Journal Article
Wäldchen, J.; Rzanny, M.; Seeland, M.; Mäder, P.: Automated plant species identification—Trends and future directions. PLoS Computational Biology 14 (4), e1005993 (2018)
34.
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Wäldchen, J.; Mäder, P.: Plant species identification using computer vision: A systematic literature review. Archives of Computational Methods in Engineering 25 (2), pp. 507 - 543 (2018)
35.
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Rzanny, M.; Seeland, M.; Wäldchen, J.; Mäder, P.: Acquiring and preprocessing leaf images for automated plant identification: understanding the tradeoff between effort and information gain. Plant Methods 13, 97 (2017)
36.
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Seeland, M.; Rzanny, M.; Alaqraa, N.; Wäldchen, J.; Mäder, P.: Plant species classification using flower images—A comparative study of local feature representations. PLoS One 12 (2), e0170629 (2017)
37.
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Wäldchen, J.; Thuille, A.; Seeland, M.; Rzanny, M.; Schulze, E. D.; Boho, D.; Alaqraa, N.; Hofmann, M.; Mäder, P.: Flora Incognita – Halbautomatische Bestimmung der Pflanzenarten Thüringens mit dem Smartphone. Landschaftspflege und Naturschutz in Thüringen 53 (3), pp. 121 - 125 (2016)

Conference Paper (1)

38.
Conference Paper
Seeland, M.; Rzanny, M.; Alaqraa, N.; Thuille, A.; Boho, D.; Wäldchen, J.; Mäder, P.: Description of flower colors for image based plant species classification. In: 22nd German Color Workshop (FWS), Ilmenau, Germany, pp. 145 - 154 (Ed. Franke, K.-H.). (2016)

Preprint (3)

39.
Preprint
Kösters, L.; Karbstein, K.; Hofmann, M.; Hodac, L.; Mäder, P.; Wäldchen, J.: Data fusion for integrative species identification using deep learning. bioRxiv: the preprint server for biology (2025)
40.
Preprint
Tarieiev, A.; Karbstein, K.; Gailing, O.: Phylogenetic and taxonomic insights into Betula: low-coverage whole genome sequencing and plastome analysis with focus on the rare Ukrainian endemic species Betula klokovii Zaverucha. bioRxiv: the preprint server for biology (2025)
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