【摘要】 现有的机器采茶都需要人工辅助进行采茶，且存在老叶、嫩芽一刀切的情况，会损害一部分茶叶，只适用于低端茶叶的采摘。因此，需要研究出一种精准高效的茶叶嫩芽识别方法。针对茶叶嫩芽图像背景复杂的问题，在YOLOv5算法的基础上，对算法进行多角度的改进，实验结果表明，改进算法的模型的mAP提升了4.1%,Recall提升了4.0%,且改进方法减少了漏检情况的发生。更多还原

【Abstract】 The existing machinery for tea picking requires manual assistance for tea picking, and there is a situation where old leaves and tender buds are cut in one piece, which can damage a portion of the tea and is only suitable for picking low end tea. Therefore, it is necessary to develop an accurate and efficient method for identifying tea buds. Aiming at the problem of complex background in tea bud images, this paper addresses the issue of complex backgrounds in images of tea bud shoots. Based on the YOLOv5 algorithm, the paper implements multifaceted improvements to the algorithm. The experimental results show that the improved model’s mean Average Precision(mAP) has increased by 4.1%, and Recall has increased by 4.0%, with the improved method reducing the occurrence of missed detections.更多还原