The Classification of Tea Leaf Disease Using CNN Image Classifier

DOI

10.2991/978-94-6463-174-6_10How to use a DOI?

Keywords

technological developments; tea leaf diseases; classification; convolutional neural networks; epochs

Abstract

Technological developments have encouraged advances in plant disease control. One plant disease that needs to be controlled quickly is tea leaf disease. Tea leaf diseases are numerous. In this study, we took 4 disease samples. Image recognition of tea leaf diseases with Convolutional Neural Networks (CNN) is necessary for classification and disease control. The disease recognition process goes through an image classification process with a classification algorithm that has been pre trained with pre-labeled image data. A good model is essential for tea leaf disease recognition. A good model can be measured by accuracy, precision, and recall in the testing process. There are several factors that effect of the model, including the dataset division ratio, the number of repetitions (epoch). In this study, a dataset of 400 data was used which was divided into 4 classes to be trained namely algal leaf, anthracnose, bird eye spot, and healthy. Based on the results of the testing process, the best accuracy of 100%, precision of 95% and recall of 24% by applying of augmentation, precision and recall in the pre-processing stage, using a dataset ratio of 70:30 and epoch 150 has an effect in increasing the accuracy value.

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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TY  - CONF
AU  - Eliana Aida Rosyidah
AU  - Alfian Futuhul Hadi
AU  - Yuliani Setia Dewi
PY  - 2023
DA  - 2023/05/22
TI  - The Classification of Tea Leaf Disease Using CNN Image Classifier
BT  - Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)
PB  - Atlantis Press
SP  - 89
EP  - 112
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-174-6_10
DO  - 10.2991/978-94-6463-174-6_10
ID  - Rosyidah2023
ER  -