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GSD-YOLO: A Lightweight Decoupled Wheat Scab Spore Detection Network Based on Yolov7-Tiny

文献类型: 外文期刊

作者: Zhang, Dongyan 1 ; Tao, Wenfeng 2 ; Cheng, Tao 1 ; Zhou, Xingen 3 ; Hu, Gensheng 2 ; Qiao, Hongbo 4 ; Guo, Wei 4 ; Wang, Ziheng 1 ; Gu, Chunyan 5 ;

作者机构: 1.Northwest A&F Univ, Coll Mech & Elect Engn, Yangling 712100, Peoples R China

2.Anhui Univ, Natl Engn Res Ctr Agroecol Big Data Anal & Applica, Hefei 230601, Peoples R China

3.Texas A&M AgriLife Res Ctr, 1509 Aggie Dr, Beaumont, TX 77713 USA

4.Henan Agr Univ, Coll Informat & Management Sci, Zhengzhou 450002, Peoples R China

5.Anhui Acad Agr Sci, Inst Plant Protect & Agroprod Safety, Hefei 230031, Peoples R China

关键词: wheat scab spores; target detection; YOLO; GSConv; decoupled head

期刊名称:AGRICULTURE-BASEL ( 影响因子:3.6; 五年影响因子:3.8 )

ISSN:

年卷期: 2024 年 14 卷 12 期

页码:

收录情况: SCI

摘要: Aimed at the problem of the difference between intra-class and inter-class pathogenic spores of Wheat Scab image being small and difficult to distinguish, in this paper, we propose a lightweight decoupled Wheat Scab spore detection network based on Yolov7-tiny (GSD-YOLO). Specifically, considering the limitations of the storage space and power consumption of actual field detection equipment, the original detection head is optimized as a decoupled head, and the GSConv lightweight module is embedded to reduce the parameters of the model and the number of calculations required. In addition, we utilize an improved Spore-Copy data augmentation strategy to improve the detection performance and generalization ability of the algorithm to fit the large numbers, morphology, and variety of wheat disease spores in the actual field and to improve the efficiency of constructing a large data set of diverse spores. The experimental results show that the mAP of the proposed algorithm reaches 98.0%, which is 3.9 percentage points higher than that of the original model. At the same time, the detection speed of the algorithm is 114 f/s, and the memory is 13.1 MB, which meets the application requirements of hardware deployment and real-time detection. It can provide some technical support to the prevention and grading of Wheat Scab in actual farmland.

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