Publications by authors named "Jianlong Luo"
Advancing jasmine tea production: YOLOv7-based real-time jasmine flower detection.
J Sci Food Agric
December 2024
Article Synopsis
- - The study focuses on improving jasmine tea quality by accurately harvesting jasmine flowers at the right growth stage, using the YOLOv7 algorithm to classify flower types based on their visual characteristics.
- - The YOLOv7 model achieved a mean average precision of 0.948, with high detection accuracy for various flower openness levels ranging from small buds to wilted flowers.
- - Findings suggest that deep learning can effectively distinguish between jasmine flowers at different stages, potentially aiding in better production practices and smarter flower-picking methods to minimize waste and costs.