{"title":"利用卷积神经网络检测玉米叶片病害:基于预训练 VGG16 架构的移动应用程序","authors":"Hansamali Paul, Hirunika Udayangani, Kalani Umesha, Nalaka Lankasena, Chamara Liyanage, Kasun Thambugala","doi":"10.1080/01140671.2024.2385813","DOIUrl":null,"url":null,"abstract":"Reliance on visual inspection for Maize leaf disease identification proves unreliable, often resulting in inappropriate pesticide application and associated health hazards. Food security requires p...","PeriodicalId":19297,"journal":{"name":"New Zealand Journal of Crop and Horticultural Science","volume":"57 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2024-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Maize leaf disease detection using convolutional neural network: a mobile application based on pre-trained VGG16 architecture\",\"authors\":\"Hansamali Paul, Hirunika Udayangani, Kalani Umesha, Nalaka Lankasena, Chamara Liyanage, Kasun Thambugala\",\"doi\":\"10.1080/01140671.2024.2385813\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reliance on visual inspection for Maize leaf disease identification proves unreliable, often resulting in inappropriate pesticide application and associated health hazards. Food security requires p...\",\"PeriodicalId\":19297,\"journal\":{\"name\":\"New Zealand Journal of Crop and Horticultural Science\",\"volume\":\"57 1\",\"pages\":\"\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2024-08-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"New Zealand Journal of Crop and Horticultural Science\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1080/01140671.2024.2385813\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"AGRONOMY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"New Zealand Journal of Crop and Horticultural Science","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1080/01140671.2024.2385813","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AGRONOMY","Score":null,"Total":0}
Maize leaf disease detection using convolutional neural network: a mobile application based on pre-trained VGG16 architecture
Reliance on visual inspection for Maize leaf disease identification proves unreliable, often resulting in inappropriate pesticide application and associated health hazards. Food security requires p...
期刊介绍:
Scope of submissions: The New Zealand Journal of Crop and Horticultural Science publishes original research papers, review papers, short communications, book reviews, letters, and forum articles. We welcome submissions on biotechnology, entomology, plant nutrition, breeding and pathology, postharvest physiology, soil science, viticulture, biosecurity, new crop and horticultural products, and descriptions of new cultivar releases. The journal welcomes work on tree and field crops, and particularly encourages contributions on kiwifruit, apples and wine grapes.