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This article presents a new approach for accurately grading the quality of fresh tea leaves using image recognition and deep learning algorithms. The proposed YOLOv8x-SPPCSPC-CBAM model outperforms other popular DL models in terms of precision, recall, and processing speed. This framework has the potential to improve the efficiency and accuracy of tea leaf grading, addressing current issues in the industry.
