Ecological Informatics
Georgia Fargetta, Stefano Anile, Luigi Priano, Massimo Orazio Spata, Alessandro Ortis, and Sebastiano Battiato are pleased to announce the publication of our article:
Bridging AI and wildlife conservation: Classifying wildcats from genetically validated images in Ecological Informatics (Elsevier, Q1 – Computer Science).
https://www.sciencedirect.com/science/article/pii/S1574954125004765
https://www.sciencedirect.com/science/article/pii/S1574954125004765
This work introduces an AI-based recognition system designed to support wildlife researchers and conservationists in the classification of wild-living cats, including European wildcats (Felis silvestris), hybrids (F. silvestris × catus), and domestic cats (F. catus), using genetically validated real-world images.
A key outcome of the study is the development of a mobile application for automatic recognition, optimized for offline field use, enabling researchers and citizen scientists to classify cat images directly on mobile devices, even in remote environments.
All resources — including the dataset, model weights, and mobile recognition app — are available upon request at the following link: https://www.dmi.unict.it/ortis/wildcat/
This research represents a successful collaboration between computer scientists, zoologists, and citizen scientists, coordinated within the EuroWildcat network, and demonstrates how artificial intelligence can effectively contribute to ecological monitoring and biodiversity conservation.
A sincere thank you to all co-authors and to the EuroWildcat research group for their essential contribution and data sharing.
