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Npj Biodiversity|September 6, 2024
Opportunistic plant observations reveal spatial and temporal gradients in phenologyMichael Rzanny, Patrick Mäder, Hans Christian Wittich, et al.
Systematic Biology|July 24, 2024
Inferring Taxonomic Affinities and Genetic Distances Using Morphological Features Extracted from Specimen Images: A Case Study with a Bivalve Data SetMartin Hofmann, Steffen Kiel, Lara M Kösters, et al.
BMC Bioinformatics|May 31, 2018
Recommending plant taxa for supporting on-site species identificationHans Christian Wittich, Marco Seeland, Jana Wäldchen, et al.
Biology|March 29, 2023
Geometric Morphometric Versus Genomic Patterns in a Large Polyploid Plant Species ComplexLadislav Hodač, Kevin Karbstein, Salvatore Tomasello, et al.
Frontiers in Plant Science|February 14, 2022
Image-Based Automated Recognition of 31 Poaceae Species: The Most Relevant PerspectivesMichael Rzanny, Hans Christian Wittich, Patrick Mäder, et al.
Frontiers in Plant Science|October 20, 2023
Bridging the gap: how to adopt opportunistic plant observations for phenology monitoringNegin Katal, Michael Rzanny, Patrick Mäder, et al.
International Journal of Biometeorology|July 4, 2025
Expanding phenological insights: automated phenostage annotation with community science plant imagesNegin Katal, Michael Rzanny, Patrick Mäder, et al.
BMC Bioinformatics|December 15, 2020
Flora Capture: a citizen science application for collecting structured plant observationsDavid Boho, Michael Rzanny, Jana Wäldchen, et al.
The Plant Journal : for Cell and Molecular Biology|October 9, 2024
Deep learning to capture leaf shape in plant images: Validation by geometric morphometricsLadislav Hodač, Kevin Karbstein, Lara Kösters, et al.
Annals of Botany|September 25, 2025
Towards the automatized identification of moss species from their spore morphologyAlix Milis, Martin Hofmann, Patrick Mäder, et al.
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