New Poultry Science Study Findings Have Been Reported by Investigators at University of Georgia (Monitoring Activity Index and Behaviors of Cage-free Hens With Advanced Deep Learning Technologies).

Researchers at the University of Georgia have developed convolutional neural network models to monitor the activity index of cage-free hens using advanced deep learning technologies. The study aimed to assess animal health and welfare by tracking chicken behaviors and activities in commercial poultry houses. The results showed that the combination of YOLOv8 and DeepSORT models had the highest performance, achieving a multiobject tracking accuracy of 94%. This research highlights the potential of deep learning in monitoring poultry activity index for evaluating animal health and welfare. [Extracted from the article]