Max Planck Gesellschaft

Research group: Flora Incognita


The aim of the “Flora Incognita” research group is to develop a method for semi-automatic plant identification via mobile devices. Challenging current standards, modern computer vision techniques such as deep neural networks will be combined to a "connected data" application, using site information (e.g. climate, geology, phenology) and plant morphological traits.


Name Position E-mail Phone Room
Jana Wäldchen Group leader jwald +49 3677 69 4849 C3.005 (tower) or TU Ilmenau
Michael Rzanny PostDoc mrzanny ...6222 C3.005 (tower)
Alice Deggelmann Scientific assistant adeggel ...6222 C3.005 (tower)
Oliver Bley Guest obley ...6379 A.. or TU Ilmenau

Current Project

Flora Incognita - interactive plant species identification with mobile devices

Flora Incognita is a research project founded by the Federal Ministry of Education and Research (BMBF), the Federal Ministry of Environment, Nature Conservation, Building and Nuclear Safty (BMUB), the Federal Agency for Nature Conservation (BfN) and the Nature Conservation Foundation of Thuringia, with the purpose to support research projects to implement the German National Strategy on Biological Diversity.It is a joint project between the Technical University in Ilmenau and the Max Planck Institute for Biogeochemistry in Jena.


  1. Developing an interactive and incremental method for the semi-automated identification of plant species
  2. Creating a repository of the wild flowering plants of middle Germany customized to specifics of automated recognition
  3. Developing didactically optimized user interactions and species information within the identification process
  4. Developing an automated field mapping system for the identified plant species and their registration within central databases of the Nature Conservation authorities

On the project website you will find information on the Flora Incognita organization, the latest news and how to join Flora Incognita activities.

Key papers

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: 97. doi:10.1186/s13007-017-0245-8.
(internal: final.pdf )
Seeland, M., Rzanny, M., Alaqraa, N., Wäldchen, J., Mäder, P. (2017). Plant species classification using flower images—A comparative study of local feature representations. PLoS One, 12(2): e0170629. doi:10.1371/journal.pone.0170629.
(internal: final.pdf final.pdf )
Wäldchen, J., Mäder, P. (2018). Plant species identification using computer vision: A systematic literature review. Archives of Computational Methods in Engineering, 25(2), 507-543. doi:10.1007/s11831-016-9206-z.
(internal: final.pdf )

Follow link for a complete list of publications by the research group.

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