已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Detection of cucumber downy mildew spores based on improved YOLOv5s

霜霉病 孢子 古巴假孢霉 霉病 环境科学 生物 植物 工程类
作者
Qiao Chen,Kaiyu Li,Xinyi Zhu,Jiaping Jing,Wei Gao,Lingxian Zhang
出处
期刊:Information Processing in Agriculture [Elsevier BV]
被引量:1
标识
DOI:10.1016/j.inpa.2024.05.002
摘要

Cucumber downy mildew is caused by the infection of leaves with downy mildew spores. However, research on the prevention and control of cucumber downy mildew often focuses on the stage after symptoms have appeared on the leaves, that is, once disease spots have already formed. Since the occurrence of downy mildew is closely related to the quantity of spores, early-stage research on the quantity of downy mildew spores is of great significance for the prevention and control of cucumber downy mildew. Consequently, developing a rapid, accurate, and efficient method for detecting cucumber downy mildew spores is critical for advancing disease control. This study introduces an improved YOLOv5s model for spore detection. The model incorporates a transformer module into YOLOv5s's backbone, enhancing global feature information extraction. It also adds a small object detection head to counter YOLOv5s's extensive down-sampling and difficulty in learning features of small objects. Integration with the Convolutional Block Attention Module (CBAM) further refines detection precision for small objects like mildew spores. Upon evaluation with an image dataset collected through a microscope, the improved YOLOv5s model demonstrated superior performance metrics across various resolutions. At a resolution of 1440px × 1440px, it achieved the highest mean Average Precision ([email protected]) of 95.4 %, a precision (P) score of 89.1 %, and a recall (R) rate of 90.3 %. These metrics surpassed the original YOLOv5s model at the same 1440px × 1440px resolution by 1.6 % in [email protected], 1.6 % in P, and 0.5 % in R. Additionally, the model's [email protected] across various resolution scales indicates superior detection precision compared to other leading models like YOLOv7. In the context of microscopic images with small spores and complex backgrounds, the improved YOLOv5s model effectively detects cucumber downy mildew spores, offering valuable insights and technical support for advancing the prevention and control measures against cucumber downy mildew.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
哐哧哐哧薯完成签到 ,获得积分10
刚刚
柠萌绿发布了新的文献求助10
1秒前
科研通AI2S应助魔幻若血采纳,获得10
1秒前
村长发布了新的文献求助10
2秒前
科研通AI2S应助科研通管家采纳,获得10
2秒前
科目三应助科研通管家采纳,获得10
2秒前
打打应助科研通管家采纳,获得10
2秒前
慕青应助科研通管家采纳,获得10
2秒前
Criminology34应助科研通管家采纳,获得10
2秒前
斯文败类应助科研通管家采纳,获得10
2秒前
充电宝应助科研通管家采纳,获得10
2秒前
CipherSage应助科研通管家采纳,获得10
3秒前
852应助科研通管家采纳,获得10
3秒前
英俊的铭应助科研通管家采纳,获得30
3秒前
科研通AI2S应助科研通管家采纳,获得10
3秒前
3秒前
3秒前
5秒前
衷医课代表完成签到,获得积分10
5秒前
喜悦又菡完成签到,获得积分10
5秒前
杜雨柔发布了新的文献求助10
6秒前
馆长举报blal求助涉嫌违规
6秒前
丘比特应助three采纳,获得10
7秒前
johnnylee发布了新的文献求助10
8秒前
Flow3ry完成签到,获得积分10
10秒前
11秒前
12秒前
12秒前
喜悦又菡发布了新的文献求助10
12秒前
13秒前
15秒前
善学以致用应助陈诚采纳,获得30
15秒前
纯纯牛马发布了新的文献求助30
17秒前
ABCD发布了新的文献求助10
17秒前
细心语琴应助Hikah采纳,获得30
18秒前
科研通AI6应助Duliang_zhao采纳,获得10
18秒前
唐若冰完成签到,获得积分10
18秒前
19秒前
完美世界应助张佳佳采纳,获得10
19秒前
NexusExplorer应助泓竹采纳,获得10
20秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Comprehensive Methanol Science Production, Applications, and Emerging Technologies 1200
Architectural Corrosion and Critical Infrastructure 1000
Early Devonian echinoderms from Victoria (Rhombifera, Blastoidea and Ophiocistioidea) 1000
By R. Scott Kretchmar - Practical Philosophy of Sport and Physical Activity - 2nd (second) Edition: 2nd (second) Edition 666
Electrochemistry: Volume 17 600
Physical Chemistry: How Chemistry Works 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 4943657
求助须知:如何正确求助?哪些是违规求助? 4208947
关于积分的说明 13084244
捐赠科研通 3988330
什么是DOI,文献DOI怎么找? 2183567
邀请新用户注册赠送积分活动 1199094
关于科研通互助平台的介绍 1111805