A new scientific publication by researchers from the University of Donja Gorica and DunavNET explores the use of GenAI in digital agriculture.
Published as Evaluating the FLUX.1 Synthetic Data on YOLOv9 for AI-Powered Poultry Farming in the Journal Applied Sciences MDPI, this study demonstrates how synthetic data, generated using FLUX.1, enhances deep learning models for chicken detection in smart farms. The findings show that combining real and AI-generated images improves detection accuracy, reducing the need for extensive manual data collection and enabling more efficient farm automation.
Supported by the HPC4S3ME IPA project and the National Competence Center for HPC in Montenegro (EuroCC2, EuroCC4SEE), this research highlights the role of high-performance computing and AI in advancing agricultural innovation.
Authored by Stevan Čakić, Tomo Popović, Srđan Krčo, Ivan Jovović, and Dejan Babić.
Read the full paper here.
