Autonomous Mobile Robot for Apple Plant Disease Detection based on CNN and Multi-Spectral Vision System

Pavel Karpyshev, Valery Ilin, Ivan Kalinov, Alexander Petrovsky, Dzmitry Tsetserukou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2021 IEEE/SICE International Symposium on System Integration, SII 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages157-162
Number of pages6
ISBN (Electronic)9781728176581
DOIs
Publication statusPublished - 11 Jan 2021
Event2021 IEEE/SICE International Symposium on System Integration, SII 2021 - Virtual, Iwaki, Fukushima, Japan
Duration: 11 Jan 202114 Jan 2021

Publication series

Name2021 IEEE/SICE International Symposium on System Integration, SII 2021

Conference

Conference2021 IEEE/SICE International Symposium on System Integration, SII 2021
Country/TerritoryJapan
CityVirtual, Iwaki, Fukushima
Period11/01/2114/01/21

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