Project DetailsClassifying dairy cows is a critical operation for dairy farms. The primary goal of dairy farms is to maximize milk production, which is achieved by monitoring various aspects of each cow, including milk yield, health status, estrus time, and other characteristics. Therefore, the foremost objective of a dairy farm is to establish a reliable method for identifying each cow accurately.
Currently, common methods for cow identification rely on permanent measures such as ear or back tattooing, as well as the use of ear tags equipped with radio frequency identification (RFID) technology. However, these methods have limitations as they can fade, fall off, or break over time.
In this work, we developed a real-time cow identification system based on computer vision and neural networks. We implemented and tested five different solutions and conducted a comprehensive comparison of their results. Through this comparison, we highlighted the trade-offs between the different approaches.
