Performance comparison of convolutional neural network models for plant leaf disease classification
[ X ]
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
As food is an essential element in life, modern possibilities must be harnessed to pay attention to it. In this paper, we will discuss the discovery of early plant diseases classification using artificial intelligence technology, we made in this study analysis of convolutional neural networks architecture (vgg-16, mobile net, efficient net) and made a comparison between these model in accuracy and loos data in each model, we used data set from the Kaggle site that contain 20640 picture from different disease of plant (potato, tomato and pepper) this pictures divided on 15 class but unbalanced. at the first we solved the problem of train the models with multi class, we made balanced data and training the work in environment of Google Colab, we used it in train three models vgg-16, mobile net, efficient net, which showed this study that the accuracy of work in efficient net is 98% more than other models and loss data in this model is less than other models.
Açıklama
Anahtar Kelimeler
Efficient Net, Google Colab, Mobile Net, Transform Learning, Vgg-16
Kaynak
ISMSIT 2022 - 6th International Symposium on Multidisciplinary Studies and Innovative Technologies, Proceedings
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Al Heeti, F., Ilyas, M. (2022). Performance comparison of convolutional neural network models for plant leaf disease classification. In 2022 International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 386-391). IEEE.
