Plant Disease Detection using Image Processing

Anupama Mishra, Priyanka Chaurasia, Varsha Arya, Francisco Jos´e Garc´ıa Pe˜nalvo

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

328 Downloads (Pure)

Abstract

Plant diseases have an impact on the development of their particular species, hence early detection is crucial. Numerous Machine Learning (ML) models have been used for the identification and classification of plant diseases, this field of study now appears to have significant potential for improved accuracy. In order to identify and categorise the signs of plant diseases, numerous developed/modified ML architectures are used in conjunction with a number of visualisation techniques. Additionally, a number of performance indicators are employed to assess these structures and methodologies.
Original languageEnglish
Title of host publicationInternational Conference on Cyber Security, Privacy and Networking (ICSPN 2022)
Pages227-235
Number of pages9
ISBN (Electronic)978-3-031-22018-0
DOIs
Publication statusPublished online - 21 Feb 2023
EventInternational Conference on Cyber Security, Privacy and Networking - Bangkok, Thailand
Duration: 9 Sept 202211 Sept 2022
https://cyber-conf.com/icspn2022/

Publication series

NameLecture Notes in Networks and Systems
Volume599 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

ConferenceInternational Conference on Cyber Security, Privacy and Networking
Abbreviated titleICSPN 2022
Country/TerritoryThailand
CityBangkok
Period9/09/2211/09/22
Internet address

Bibliographical note

Funding Information:
Acknowledgement. This research was partially funded by the Spanish Government Ministry of Science and Innovation through the AVisSA project grant number (PID2020-118345RB-I00).

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Plant disease, Machine learning
  • Plant disease
  • Machine learning

Fingerprint

Dive into the research topics of 'Plant Disease Detection using Image Processing'. Together they form a unique fingerprint.

Cite this