Apple Trees Diseases Detection through Computer Vision in Embedded Systems

Denis Logashov, Dmitrii Shadrin, Andrey Somov, Mariia Pukalchik, Anastasia Uryasheva, Hari Prabhat Gupta, Nikita Rodichenko

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

1 Citation (Scopus)

Abstract

In this paper, we address the problem of detecting diseases of apple trees. We report on a computer vision method for apple trees leaves segmentation. For this reason we collect the leaves images in the field using a thermal image camera. Data analysis is carried out using Neural Networks (NN) optimized for running on the embedded systems. We perform a comparative study on the embedded systems, embedded systems enriched with the GPU capability, and the PC. We achieved IoU=0.814. Our results demonstrate that the NNs running on the embedded systems is a promising solution for detecting the trees diseases using embedded systems and open up wide vista for its application in precision agriculture.

Original languageEnglish
Title of host publicationProceedings of 2021 IEEE 30th International Symposium on Industrial Electronics, ISIE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728190235
DOIs
Publication statusPublished - 20 Jun 2021
Event30th IEEE International Symposium on Industrial Electronics, ISIE 2021 - Kyoto, Japan
Duration: 20 Jun 202123 Jun 2021

Publication series

NameIEEE International Symposium on Industrial Electronics
Volume2021-June

Conference

Conference30th IEEE International Symposium on Industrial Electronics, ISIE 2021
Country/TerritoryJapan
CityKyoto
Period20/06/2123/06/21

Keywords

  • Computer vision
  • disease detection
  • embedded systems
  • precision agriculture

Fingerprint

Dive into the research topics of 'Apple Trees Diseases Detection through Computer Vision in Embedded Systems'. Together they form a unique fingerprint.

Cite this