Publikationen von Jana Wäldchen
Alle Typen
Zeitschriftenartikel (40)
1.
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More than rapid identification—Free plant identification apps can also be highly accurate. People and Nature (2024)
2.
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Deep learning to capture leaf shape in plant images: Validation by geometric morphometrics. The Plant Journal (2024)
3.
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From unwanted to wanted: Blending functional weed traits into weed distribution maps. Weed Research (2024)
4.
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Inferring taxonomic affinities and genetic distances using morphological features extracted from specimen images: a case study with a bivalve data set. Systematic Biology (2024)
5.
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39 (8), S. 771 - 784 (2024)
Species delimitation 4.0: integrative taxonomy meets artificial intelligence. Trends in Ecology and Evolution 6.
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15 (8), S. 1422 - 1437 (2024)
Macrophenological dynamics from citizen science plant occurrence data. Methods in Ecology and Evolution 7.
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44 (5), tpae045 (2024)
Parametrization of biological assumptions to simulate growth of tree branching architectures. Tree Physiology 8.
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379 (1904), 20230106 (2024)
Emerging technologies in citizen science and potential for insect monitoring. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences 9.
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3, 5 (2024)
Opportunistic plant observations reveal spatial and temporal gradients in phenology. npj Biodiversity 10.
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54 (1), S. 29 - 31 (2024)
Flora Incognita – mehr als Pfanzenbestimmung. Biologie in unserer Zeit 11.
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14, 1150956 (2023)
Bridging the gap: How to adopt opportunistic plant observations for phenology monitoring. Frontiers in Plant Science 12.
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98 (6+7), S. 304 - 311 (2023)
Künstliche Intelligenz im Naturschutz. Natur und Landschaft 13.
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10, 168 (2023)
The HAInich: A multidisciplinary vision data-set for a better understanding of the forest ecosystem. Scientific Data 14.
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12 (3), 418 (2023)
Geometric morphometric versus genomic patterns in a large polyploid plant species complex. Biology 15.
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4 (6), S. 1603 - 1615 (2022)
Towards more effective identification keys: A study of people identifying plant species characters. People and Nature 16.
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37 (10), S. 872 - 885 (2022)
Emerging technologies revolutionise insect ecology and monitoring. Trends in Ecology and Evolution 17.
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13, 805738 (2022)
Deep learning in plant phenological research: A systematic literature review. Frontiers in Plant Science 18.
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12, 804140 (2022)
Image-based automated recognition of 31 Poaceae species: The most relevant perspectives. Frontiers in Plant Science 19.
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44 (8), S. 1131 - 1142 (2021)
Crowd-sourced plant occurrence data provide a reliable description of macroecological gradients. Ecography 20.
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13 (4), plab050 (2021)
Plant image identification application demonstrates high accuracy in Northern Europe. AOB PLANTS