山东农业科学2024，Vol.56Issue(3)：154-162,9.DOI:10.14083/j.issn.1001-4942.2024.03.021
基于特征融合注意力机制的樱桃缺陷检测识别研究
Research on Cherry Defect Detection and Recognition Based on Feature Fusion Attention Mechanism
摘要
Abstract
In view of the existing problems in cherry defect detection and recognition,and to realize in-telligent rapid detection and accurate recognition,a lightweight defect detection and recognition model based on convolutional neural network was proposed for cherry images,which could provide a theoretical basis for developing lossless intelligent detection system carried on mobile terminal.Firstly,the collected images of in-tact cherries,growth-stimulated cherries,twin cherries and rotten cherries were preprocessed,and then were divided into training,validation and test sets in proportion.Secondly,after comparing the network models such as NASNet-Mobile,MobileNetV2,ResNet18,InceptionV3 and VGG-16 based on transfer learning,the Mo-bileNetV2 with good performance in all aspects was selected as the baseline model,and then the I-Mobile-NetV2 model was established after fine tuning.On the basis of I-MobileNetV2,the coordinate attention was embedded,and then the ICA-MobileNetV2 model was constructed.The average accuracy of ICA-MobileNetV2 model reached 97.09% ,which was 7.85% higher than that of baseline model(90.02% )and 2.91% higher than that of I-MobileNetV2 model(94.34% ).As a deployable lightweight model,ICA-MobileNetV2 had high-er accuracy and fewer parameters,so it was suitable for cherry defect detection and multi-classification tasks,which provided a new idea for cherry defect detection and quality classification research.关键词
樱桃/缺陷检测/卷积神经网络/坐标注意力机制Key words
Cherry/Defect detection/Convolutional neural network/Coordinate attention mechanism分类
农业科技引用本文复制引用
代东南,马睿,刘起,孙孟研,马德新..基于特征融合注意力机制的樱桃缺陷检测识别研究[J].山东农业科学,2024,56(3):154-162,9.基金项目
山东省自然科学基金项目(ZR2022MC152) （ZR2022MC152）
山东省高等学校青创人才引育计划项目(202202027) （202202027）
