Classification of Strawberry Plant Diseases with Leaf Image Using CNN

Muhammad Imam Dinata, Supeno Mardi Susiki Nugroho, Reza Fuad Rachmadi

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

6 Citations (Scopus)

Abstract

Strawberry plant is one of fruit plants that can grow in the highland with an altitude of 1000-1500m above sea level. Good care is taken to overcome diseases in strawberry plants. Farmers are usually difficult to distinguish the type of disease in strawberry plants. Deep learning is one of the ways to distinguish the types of diseases in plants by processing image feature extraction. Convolutional Neural Network (CNN) is one of the methods used in deep learning to classify diseases in strawberry plants by extracting image features of strawberry leaf disease. In this study, we propose a deep learning method using CNN to classification 6 types of diseases in strawberry plants with the use of 4663 strawberry leaf disease image data. The result of accuracy is 63,7%.

Original languageEnglish
Title of host publicationICAICST 2021 - 2021 International Conference on Artificial Intelligence and Computer Science Technology
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages68-72
Number of pages5
ISBN (Electronic)9781665424042
DOIs
Publication statusPublished - 29 Jun 2021
Event2021 International Conference on Artificial Intelligence and Computer Science Technology, ICAICST 2021 - Virtual, Online
Duration: 29 Jun 2021 → …

Publication series

NameICAICST 2021 - 2021 International Conference on Artificial Intelligence and Computer Science Technology

Conference

Conference2021 International Conference on Artificial Intelligence and Computer Science Technology, ICAICST 2021
CityVirtual, Online
Period29/06/21 → …

Keywords

  • Convolutional Neural Network
  • Deep Learning
  • Strawberry Plant Disease
  • classification

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