1. Computer Vision and Machine Learning in Ecology
Joachim Denzler
Computer Vision Group & Michael Stifel Center Jena for Data Driven and Simulation Science
Friedrich Schiller University Jena

2. Personal Background
Diploma (1992), PhD (1997), Habilitation (2003) in Computer Science from Friedrich-Alexander University Erlangen-Nuremberg, Germany
: Associate Professor, Computer Vision, University Passau
Since 2004: Professor, Chair for Digital Image Processing, Friedrich Schiller University Jena
Since 2015: Managing Director, Michael Stifel Center Jena
Member of Educational Advisory Board Spectronet (since 2008), Technical Committee Deutsche Arbeitsgemeinschaft Mustererkennung (since 2015), Member of Scientific Advisory Board, Jenoptik AG (since 2016)
Faculty Member IMPRS gBGC, IDiv, Jena School of Microbial Communication, Abbe School of Photonics

4. Links to „Computer Science meets Ecology“
Continuous observations from different sensors are possible today to monitor the ecosystem of our planet
Huge amount of data prohibits manual analysis, while selective analysis leads to bias in the results
Automatic monitoring by computer vision and machine learning methods might
lead to deeper insight into the processes while reducing manual effort
be an important aspect of data modeling life cycle
allow detection of relevant, surprising, novel aspects in/of the data
Current activities: part of BioMD, H2020 BACI, and several other collaborations in biodiversity research
Challenging real-world application to apply, improve, and develop computer vision and machine learning methods