Pavel A. Karpyshev, V. Ilin, I. Kalinov, Alexander Petrovsky, D. Tsetserukou
{"title":"基于CNN和多光谱视觉系统的苹果植物病害自主移动机器人","authors":"Pavel A. Karpyshev, V. Ilin, I. Kalinov, Alexander Petrovsky, D. Tsetserukou","doi":"10.1109/IEEECONF49454.2021.9382649","DOIUrl":null,"url":null,"abstract":"This paper presents an autonomous system for apple orchard inspection and early stage disease detection. Various sensors including hyperspectral, multispectral and visible range scanners are used for disease detection. For localization and obstacle detection 2D LiDARs and RTK GNSS receivers are used. The proposed system allows to minimize the use of pesticides and increase harvests. The detection approach is based on the use of neural networks for both plant segmentation and disease detection.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"Autonomous Mobile Robot for Apple Plant Disease Detection based on CNN and Multi-Spectral Vision System\",\"authors\":\"Pavel A. Karpyshev, V. Ilin, I. Kalinov, Alexander Petrovsky, D. Tsetserukou\",\"doi\":\"10.1109/IEEECONF49454.2021.9382649\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an autonomous system for apple orchard inspection and early stage disease detection. Various sensors including hyperspectral, multispectral and visible range scanners are used for disease detection. For localization and obstacle detection 2D LiDARs and RTK GNSS receivers are used. The proposed system allows to minimize the use of pesticides and increase harvests. The detection approach is based on the use of neural networks for both plant segmentation and disease detection.\",\"PeriodicalId\":395378,\"journal\":{\"name\":\"2021 IEEE/SICE International Symposium on System Integration (SII)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE/SICE International Symposium on System Integration (SII)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEECONF49454.2021.9382649\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE/SICE International Symposium on System Integration (SII)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEECONF49454.2021.9382649","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Autonomous Mobile Robot for Apple Plant Disease Detection based on CNN and Multi-Spectral Vision System
This paper presents an autonomous system for apple orchard inspection and early stage disease detection. Various sensors including hyperspectral, multispectral and visible range scanners are used for disease detection. For localization and obstacle detection 2D LiDARs and RTK GNSS receivers are used. The proposed system allows to minimize the use of pesticides and increase harvests. The detection approach is based on the use of neural networks for both plant segmentation and disease detection.