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

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The Comparison of Convolutional Neural Networks Architectures on Classification Potato Leaf Diseases

Authors
Rifki Ilham Baihaki1, Dafik1, 2, Ika Hesti Agustin1, 3, Zainur Rasyid Ridlo1, 4, *, Elsa Yuli Kurniawati1
1PUI-PT Combinatorics and Graph, CGANT, University of Jember, Jember, Indonesia
2Departement of Mathematics Education Postgraduate, University of Jember, Jember, Indonesia
3Departement of Mathematics, University of Jember, Jember, Indonesia
4Department of Science Education, University of Jember, Jember, Indonesia
*Corresponding author. Email: zainur.fkip@unej.ac.id
Corresponding Author
Zainur Rasyid Ridlo
Available Online 22 May 2023.
DOI
10.2991/978-94-6463-174-6_12How to use a DOI?
Keywords
smart agricultural; leaf disease image classification; deep neural networks
Abstract

Potato is a plant from the Solanaceae tribe and one of the staple crops for human consumption. Potatoes have several benefits such as being low in fat and having a better carbohydrate content than rice. Behind the relatively easy cultivation of potato plants, there are problems that are often faced by farmers. This problem is the susceptibility of potato plants to disease. An emerging solution is to combine computer vision and deep learning. This research compared four deep learning architectures such as Alexnet, GoogleNet, ResNet-50, and VGG-16. The best model was produced by VGG-16 with a test accuracy of 99.67%.

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_12How 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  - Rifki Ilham Baihaki
AU  - Dafik
AU  - Ika Hesti Agustin
AU  - Zainur Rasyid Ridlo
AU  - Elsa Yuli Kurniawati
PY  - 2023
DA  - 2023/05/22
TI  - The Comparison of Convolutional Neural Networks Architectures on Classification Potato Leaf Diseases
BT  - Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)
PB  - Atlantis Press
SP  - 125
EP  - 145
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-174-6_12
DO  - 10.2991/978-94-6463-174-6_12
ID  - Baihaki2023
ER  -