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.
|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|
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.
On the project website you will find information on the Flora Incognita organization, the latest news and how to join Flora Incognita activities. http://floraincognita.com/
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.
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
Wäldchen, J. & Mäder, P. (2017): Plant Species Identification Using Computer Vision Techniques: A Systematic Literature Review. Archives of Computational Methods in Engineering. doi:10.1007/s11831-016-9206-z