包装与食品机械2026，Vol.44Issue(2)：81-90,10.DOI:10.3969/j.issn.1005-1295.2026.02.009
基于D-Fine的棒棒糖微缺陷检测算法
Micro-defect detection algorithm for lollipops based on D-Fine
摘要
Abstract
To address the challenges in candy defect detection,where traditional models suffer from insufficient accuracy,large parameter counts,and slow inference speeds that fail to meet the real-time quality control requirements of high-speed production lines,an LRF-DFine detection algorithm integrating three core innovative modules is proposed,based on the D-Fine model.While preserving the original structure and foundation of the D-Fine model,the RepGhostCSPELAN lightweight module is incorporated to simplify the model and improve inference speed.The FMFFN mid-frequency feature enhancement module and the SimAM attention optimization module are utilized to suppress background interference and highlight critical regions.Experimental results show that,compared to the overall detection performance of the D-Fine model,the LRF-DFine model achieves comprehensive optimization in detection performance.Precision and recall are improved by 3.6 and 3.4 percentage points,respectively;mAP@0.5 is increased by 3.3 percentage points,and mAP@0.5∶0.95 is increased by 2.0 percentage points.The parameter count is reduced by 35.3%,computational complexity is decreased by 27.2%,and inference speed is increased by 20.0%.This research provides an effective technical solution for automated quality control in the food industry.关键词
糖果/微缺陷检测/D-Fine模型/小目标/注意力机制Key words
candy/micro-defect detection/D-Fine model/small objects/attention mechanism分类
轻工纺织引用本文复制引用
仲智阳,李宁冉,朱金超,朱婷婷,倪超..基于D-Fine的棒棒糖微缺陷检测算法[J].包装与食品机械,2026,44(2):81-90,10.基金项目
江苏省产学研合作项目(BY20230943) （BY20230943）
