Applications of deep learning in tea quality monitoring: a review

This review aims to summarize the application of DL technologies for tea quality assessment in three stages: cultivation, tea processing, and product evaluation, indicating that DL, with its end-to-end analytical capability and strong generalization performance, can serve as a powerful tool to support various sensing technologies for accurate tea quality detection.