Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)

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Application of Convolutional Neural Network for Identifying Cocoa Leaf Disease

Authors
Annisa Fitri Maghfiroh Harvyanti1, Rifki Ilham Baihaki2, Dafik2, 3, Zainur Rasyid Ridlo2, 4, Ika Hesti Agustin1, 2, *
1Department of Mathematics, University of Jember, Jember, Indonesia
2PUI-PT Combinatorics and Graph, CGANT, University of Jember, Jember, Indonesia
3Department of Mathematics Education Postgraduate, University of Jember, Jember, Indonesia
4Department of Science Education, University of Jember, Jember, Indonesia
*Corresponding author. Email: ikahesti.fmipa@unej.ac.id
Corresponding Author
Ika Hesti Agustin
Available Online 22 May 2023.
DOI
10.2991/978-94-6463-174-6_21How to use a DOI?
Keywords
precision agriculture; cocoa leaf disease; image classification; convolutional neural network
Abstract

Cocoa or Theobroma cacao L. is a plantation product that has high economic value and is very popular for its processed fruit. The large market demand for cocoa is not proportional to the low level of productivity. The main issue in cocoa plantations is the high incidence and rapid spread of disease. The most common disease is Vascular Streak Dieback (VSD). Appropriate treatment must be carried out immediately to maintain productivity. Identifying diseases based on leaf image using a Convolutional Neural Network (CNN) can simplify and speed up the detection of diseases. This study compares four CNN architectures, namely AlexNet, SqueezeNet, Darknet, and modified CNN to identify cocoa plants infected with VSD. The total number of datasets used is 1200 images, consisting of 600 images for the healthy class and the remaining 600 images for the VSD class. The best results were obtained with the DarkNet-19 model, with a test accuracy of 98.61%.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)
Series
Advances in Intelligent Systems Research
Publication Date
22 May 2023
ISBN
978-94-6463-174-6
ISSN
1951-6851
DOI
10.2991/978-94-6463-174-6_21How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Annisa Fitri Maghfiroh Harvyanti
AU  - Rifki Ilham Baihaki
AU  - Dafik
AU  - Zainur Rasyid Ridlo
AU  - Ika Hesti Agustin
PY  - 2023
DA  - 2023/05/22
TI  - Application of Convolutional Neural Network for Identifying Cocoa Leaf Disease
BT  - Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)
PB  - Atlantis Press
SP  - 283
EP  - 304
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-174-6_21
DO  - 10.2991/978-94-6463-174-6_21
ID  - Harvyanti2023
ER  -