摘要
Abstract
Aiming at the issues of relatively low detection accuracy and slow detection speed in fruit recognition,this paper proposes a fruit classification and detection algorithm named YOLOv11n-Triplet,incorporating the Triplet Attention mechanism.The Triplet At-tention mechanism is applied to the front of each of the three detection heads,enhancing the model's capability to represent correlations between objects and contextual information.Experimental results demonstrate that,compared to the baseline YOLOv11n model,YO-LOv11n-Triplet achieves an increase in accuracy by 4.1%,1.7%improvement in mean average precision(mAP),and 1.7%rise in recall.This provides valuable references for fruit classification research.关键词
注意力机制/目标识别/水果分类/YOLOKey words
Attention mechanism/Object detection/Fruit classification/YOLO分类
信息技术与安全科学
