改进YOLOv8n的花生品质检测方法  

Improved Peanut Quality Detection Method of YOLOv8n

作　　者：黄英来[1] 牛达伟 侯畅[1] 杨柳松[1] HUANG Yinglai;NIU Dawei;HOU Chang;YANG Liusong(College of Computer and Control Engineering,Northeast Forestry University,Harbin 150040,China)

机构地区：[1]东北林业大学计算机与控制工程学院,哈尔滨150040

出　　处：《计算机工程与应用》2024年第23期257-267,共11页Computer Engineering and Applications

基　　金：国家自然科学基金(32271781)。

摘　　要：花生品质筛选在农业生产和食品安全中具有重要意义。针对传统花生品质筛选方法效率低的问题,提出改进YOLOv8n算法的轻量化花生品质检测模型LE-YOLO(lightweight and efficient)。提出一种分组重序颈部模块(grouped shuffling bottleneck,GSBottleneck),增加了模型非线性拟合能力,减少了模型推理时间;设计了残差分组重序模块(residual group shuffling block,ResGSBlock),并结合GSConv(grouped shuffle convolution)构建轻量颈部网络(lightweight neck,LW-Neck),减少了模型计算成本,提升了模型推理速度;提出自适应特征优化模块(adaptive feature optimization block,AFOB),增强了通道间信息交互和模型表征能力。在DW花生数据集上进行实验验证,相较于YOLOv8n算法,LE-YOLO的计算量减少了1 GFlops,FPS提升了25%,平均精度均值mAP@0.5达到了98%,验证了该算法在检测精度和速度上的良好性能,为花生品质筛选提供了一种有效的方法。Peanut quality screening is of great significance in agricultural production and food safety.In order to solve the problem of low efficiency of traditional peanut quality screening methods,a lightweight peanut quality detection model LE-YOLO(lightweight and efficient)with improved YOLOv8n algorithm is proposed.A grouped shuffling bottleneck(GSBottleneck)module is proposed,which increases the nonlinear fitting ability of the model and reduces the model infer-ence time.A residual group shuffling block(ResGSBlock)is designed,and a lightweight neck(LW-Neck)is constructed by combining GSConv(grouped shuffle convolution),which reduces the cost of model calculation and improves the infer-ence speed of the model.An adaptive feature optimization block(AFOB)is proposed to enhance the information interac-tion and model characterization capabilities between channels.Experimental verification on the DW peanut dataset shows that compared with the YOLOv8n algorithm,the computational cost of LE-YOLO is reduced by 1 GFlops,the FPS is increased by 25%,and the average accuracy reaches 98%mAP@0.5,which verifies the good performance of the algo-rithm in detection accuracy and speed,and provides an effective method for peanut quality screening.

关 键 词：YOLOv8n GSConv GSBottleneck 花生品质筛选 轻量化模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]