无线电工程2024，Vol.54Issue(1)：71-77,7.DOI:10.3969/j.issn.1003-3106.2024.01.010
基于MHSA-YOLOv7的小麦赤霉病感染率检测
Detection of Gibberella Infection Rate in Wheat Based on MHSA-YOLOv7
摘要
Abstract
In disease resistance breeding,the infection rate of gibberella in wheat is an important indicator to measure the phenotype identification of grain resistance.In view of the problems of long detection time,high hardware cost and damage to plants in the detection of wheat gibberella infection,a deep learning network model,or MHSA-YOLOv7 suitable for the detection of small objects such as wheat ear grain is designed.By integrating the Muti-Head Self-Attention(MHSA)mechanism in the original YOLOv7 backbone network,the model can extract deep semantic features,and the weighted Bidirectional Feature Pyramid Network(BiFPN)is used to realize the cross-layer connection between modules,so that the model can extract and transmit richer feature information.The experimental results show that MHSA-YOLOv7 achieves a detection accuracy of 90.75%on the wheat single ear gibberella dataset.Compared with the original YOLOv7 model,the improved algorithm has stronger feature extraction ability for small objects such as wheat ear grain,and the detection Accuracy,Recall,F1 score,mAP@0.5 and mAP@0.5:0.95 are improved by 0.33%,1.83%,0.011,1.19%and 0.38%respectively.The improved algorithm effectively satisfies the accurate detection of wheat gibberella infection rate,and provides technical support for long-term observation of wheat disease trends and accurate assessment of wheat grain resistance.关键词
多头自注意力/YOLOv7/目标检测/小麦赤霉病Key words
MHSA/YOLOv7/object detection/wheat gibberella分类
信息技术与安全科学引用本文复制引用
张正华,吴宇,金志琦..基于MHSA-YOLOv7的小麦赤霉病感染率检测[J].无线电工程,2024,54(1):71-77,7.基金项目
2022 年江苏省研究生实践创新计划(SJCX22_1708) （SJCX22_1708）
2021 年扬州市级计划-市校合作专项(YZ2021159) （YZ2021159）
2021 年扬州市产业前瞻与共性关键技术-产业前瞻研发(YZ2021016)2022 Jiangsu Provincal Postgraduate Practice Innovation Plan(SJCX22_1708) （YZ2021016）
2021 Yangzhou Municipal Plan-City-School Cooperation Project(YZ2021159) （YZ2021159）
2021 Yangzhou City's Industrial Foresight and Common Key Technologies-Industrial Prospect Research and Development(YZ2021016) （YZ2021016）
