特黄三级爱爱视频|国产1区2区强奸|舌L子伦熟妇aV|日韩美腿激情一区|6月丁香综合久久|一级毛片免费试看|在线黄色电影免费|国产主播自拍一区|99精品热爱视频|亚洲黄色先锋一区

基于對比學習的番茄葉片病害識別研究

  • 打印
  • 收藏
收藏成功


打開文本圖片集

中圖分類號:TP391.4 文獻標識碼:A 文章編號:2096-4706(2025)11-0043-06

Research on Tomato Leaf Disease Recognition Based on Contrastive Learning

HUANG Zhongping (SchoolofComputerScienceandEnginering,Anhui UniversityofScienceandTechnology,Huainan2320o,China)

Abstract: In view of the current situation that traditional Deep Learning models exhibit low recognitionaccuracy and limited generalizationabilityintheprocessoftomatoleafdiseaserecognition,thispaperproposesarecognitionmodelbased on the Supervised Contrastive Leaming method.The model proposes the AMECA module based on Channel Atention,which efectivelycapturesthedependenciesamongchanels,ehances themodel'schannelfusioabilityandimprovesthereogition performance.TheAMECAmoduleisintegratedintoResNet18modelasanimagefeatureextractor,andahigh-precisiontomato leafdiseaserecognitionmodel is trained through the Supervised ContrastiveLeamingmethod.The experimentalresultsonthe tomato leaf disease dataset show that the accuracy of the model reaches 99.198% ,which is 3.208% higher than that of the original ResNet18 model.Compared with someother traditionalConvolutional Neural Networks,ithas higher recognitionaccuracyand can beterrecognizetomato leaf diseases.Itisapplicabletotomato leafimages obtained innaturalscenes,anddemonstrates strong practicability.

Keywords: Attention Mechanism;tomato leaf disease recognition; image recognition; Contrastive Learning

0 引言

番茄是全球栽培最廣、消費量最大的蔬菜作物,中國是世界上最大的番茄生產和消費國之一,番茄生產是農民增收致富和出口創(chuàng)匯的重要途徑[]。(剩余12697字)

目錄
monitor