Abstract
Fruit is a crucial component of daily diets, emphasizing the importance of ensuring its freshness. Our proposed method utilizes YOLOv8 and SE attention mechanism for detecting the freshness of fruits. Our method balances accuracy and real-time performance while detecting the freshness of different types of fruits. The proposed method achieves an average accuracy of 87.8% and a maximum accuracy of 95.0% for detecting the freshness level of a single fruit category. Experimental results confirm the effectiveness of our proposed method in accurately detecting and localizing the freshness level of fruits, demonstrating its potential for wide application and promotion in the fruit industry.
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