Fox detection on an image shot by a phototrap.

This is a two year project, funded by the University of Florence. The research group is composed of Dr. Lorenzo Seidenari (project coordinator) of the Department of Information Engineering, Dr. Francesco Rovero of the Department of Biology, and one post-doc researcher to be recruited to join the research unit at DINFO. The involved research units from the two Departments have highly complementary scientific expertise and skills, that will be fully and evenly integrated for project implementation.

The general objective of the project is to set-up a platform to manage data on wildlife obtained from camera traps, by integrating Artificial Intelligence (AI) and computer vision with ecological tools. Camera traps are remotely-set, automatic cameras that take images and videos of passing animals, and have become, over the last 10-15 years, the tool of choice to study and monitor wild mammals across the planet. The ultimate aim of the project is to boost standardized biodiversity monitoring by offering users - from passionate citizens and researchers to protected area managers, Governmental and non-Governmental agencies - a novel tool that will address the gap between data collection and processing. This will, in turn, contribute addressing key Horizon 2020 societal challenges (see section 1.2), as particularly related to the measurements of targets of sustainable biodiversity management and conservation.

Lorenzo Seidenari
Lorenzo Seidenari
Assistant Professor of Computer Engineering

I am an Assistant Professor (Tenure Track) of Computer Engineering at the University of Florence working on Deep Learning and Computer Vision.