1. Development of Automated Rose Monitoring System with Deep Learning-based Growth Stage Classification

In cut-flower cultivation, effective production planning is essential to accommodate seasonal fluctuations in market demand. Precise rose growth stage monitoring is critical for cultivation schedule, environmental control, and harvest timing, yet current practices rely on manual observations, which are time-consuming and prone to subjectivity, limiting consistency and scalability. This study presents an automated monitoring system integrating computer vision and deep learning for objective... S. Chen