Projects & Grants

Machine learning and fuzzy logic as a tool for fast and accurate species identification based on variable source data
Project IdSGS14/PřF/2023
Main solverMgr. Stanislav Ožana, Ph.D.
Period1/2023 - 12/2023
ProviderSpecifický VŠ výzkum
AnotationThe project will focus on two main areas, the first will be the further development and improvement of methods for rapid and accurate identification of selected groups of animals. The second area will be the development of collaboration with users of previously developed applications and the analysis of tools used for citizen science. Thus, the project will directly build on ongoing theoretical and practical research that has shown the potential of methods such as species recognition from images or species identification based on occurrence and environmental data sets. The main objectives of the project will therefore be: 1. The use of fuzzy logic and machine learning in the development of the basis for an application designed to identify species using habitat features. 2. Development of the existing applications (Dragonfly Hunter CZ, Herpeto-Hunter CZ, Orthoptera Hunter CZ, Mammal Hunter CZ), extension with partial new functionalities and wider public involvement in their use. 3. Analysis of citizen science approaches. The research will be carried out in collaboration between the Department of Biology and Ecology and the Department of Informatics and Computers and the Institute for Research and Applications of Fuzzy Modelling. The output of the project will be the basis of an identification algorithm aimed at recognizing animals based on observed habitat features, refinement of existing applications, publication in an impacted scientific journal, and presentation at selected conferences.