Tea bud detection in natural environments based on YOLOv11n-WELA

Key Points

• Detection accuracy reached 95% in identifying tea buds across varying natural settings, improving agricultural practices.
• The YOLOv11n-WELA model demonstrated superior performance in real-time detection, outperforming previous versions.
• Analysis utilizing computer vision techniques led to better identification of tea buds, enhancing crop monitoring.
• This methodology may enable more efficient harvesting methods; further real-world testing is advised.