{"title":"利用卷积神经网络识别榴莲叶片病害","authors":"Jay Al Gallenero, J. Villaverde","doi":"10.1109/ICCAE56788.2023.10111159","DOIUrl":null,"url":null,"abstract":"Durian leaf disease is a severe agricultural issue in many parts of Southeast Asia, especially in the Philippines. The conventional way of detecting these diseases was through manual human eye monitoring and laboratory testing, which are crucial and time-consuming in controlling the development of these diseases. When it is present, the durian tree will not produce crops. Hence, this study has shown that a portable device embedded with the Duri Premium application was able to identify the durian leaf disease and provide treatment using Convolutional Neural Network MobileNet, a pre-trained model which suffices visual processing and would significantly help reduce the economic losses associated with the diseases such as algal spot, leaf blight, leaf spot, healthy leaf, and unknown. A total of seventy-five (75) samples were analyzed and used a confusion matrix to calculate the system's accuracy, which is 93.333%. As a result, the technique efficiently identifies the diseases mentioned above on durian leaves.","PeriodicalId":406112,"journal":{"name":"2023 15th International Conference on Computer and Automation Engineering (ICCAE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of Durian Leaf Disease Using Convolutional Neural Network\",\"authors\":\"Jay Al Gallenero, J. Villaverde\",\"doi\":\"10.1109/ICCAE56788.2023.10111159\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Durian leaf disease is a severe agricultural issue in many parts of Southeast Asia, especially in the Philippines. The conventional way of detecting these diseases was through manual human eye monitoring and laboratory testing, which are crucial and time-consuming in controlling the development of these diseases. When it is present, the durian tree will not produce crops. Hence, this study has shown that a portable device embedded with the Duri Premium application was able to identify the durian leaf disease and provide treatment using Convolutional Neural Network MobileNet, a pre-trained model which suffices visual processing and would significantly help reduce the economic losses associated with the diseases such as algal spot, leaf blight, leaf spot, healthy leaf, and unknown. A total of seventy-five (75) samples were analyzed and used a confusion matrix to calculate the system's accuracy, which is 93.333%. As a result, the technique efficiently identifies the diseases mentioned above on durian leaves.\",\"PeriodicalId\":406112,\"journal\":{\"name\":\"2023 15th International Conference on Computer and Automation Engineering (ICCAE)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 15th International Conference on Computer and Automation Engineering (ICCAE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCAE56788.2023.10111159\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 15th International Conference on Computer and Automation Engineering (ICCAE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAE56788.2023.10111159","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identification of Durian Leaf Disease Using Convolutional Neural Network
Durian leaf disease is a severe agricultural issue in many parts of Southeast Asia, especially in the Philippines. The conventional way of detecting these diseases was through manual human eye monitoring and laboratory testing, which are crucial and time-consuming in controlling the development of these diseases. When it is present, the durian tree will not produce crops. Hence, this study has shown that a portable device embedded with the Duri Premium application was able to identify the durian leaf disease and provide treatment using Convolutional Neural Network MobileNet, a pre-trained model which suffices visual processing and would significantly help reduce the economic losses associated with the diseases such as algal spot, leaf blight, leaf spot, healthy leaf, and unknown. A total of seventy-five (75) samples were analyzed and used a confusion matrix to calculate the system's accuracy, which is 93.333%. As a result, the technique efficiently identifies the diseases mentioned above on durian leaves.