陕西科技大学学报2024，Vol.42Issue(6)：190-198,9.
基于多元感受野与EResPANet的草莓病害检测算法研究
Research on strawberry disease detection algorithm based on multivariate receptive field and EResPANet
摘要
Abstract
Aiming at the problem that strawberry disease images are difficult to be accurately detected due to the complex background and small targets during detection,this paper propo-ses a strawberry disease detection algorithm based on multivariate receptive field and ER-esPANet.First,the algorithm uses the multivariate receptive field feature calibration network to replace the backbone network of YOLOv7-Tiny,suppresses the redundant information,and solves the problem of small target disease loss during the layer-by-layer extraction of the features of the backbone network;finally,through the design of the EResPANet network,it avoids the problem that the target information of the network is interfered with by the com-plex background during the deep feature extraction,which leads to the problem of non-detec-tion.The experimental results show that the method proposed in this paper improves 10.3％in mAP compared with the standard YOLOv7-Tiny algorithm,which proves that the algorithm in this paper can realize the accurate detection of various types of diseases in strawberry.关键词
草莓病害/目标检测/YOLOv7-Tiny/多元感受野/EResPANet多尺度融合网络Key words
strawberry disease/object detection/YOLOv7-Tiny/the multivariate receptive fields/the EResPANet multiscale fusion network分类
信息技术与安全科学引用本文复制引用
亢洁,刘佳,王佳乐,夏宇,刘文波,李明辉..基于多元感受野与EResPANet的草莓病害检测算法研究[J].陕西科技大学学报,2024,42(6):190-198,9.基金项目
国家自然科学基金项目(62203285) （62203285）
陕西省自然科学基础研究计划项目(2022JQ-181) （2022JQ-181）
陕西省重点研发计划项目(2023-YBGY-409) （2023-YBGY-409）
西安市科技计划项目(23NYGG0070) （23NYGG0070）
