Detection of Plant Disease From Plant Image
Özet
Plants are of great importance in providing
ecological balance. They are not only a source of
nutrients but also a source of oxygen. Therefore, plants
need to be protected. By looking at the appearance of a
leaf one can decide what disease it has. With early
detection of the disease in plants, excessive damage can
be prevented. For this purpose we implemented a
method to detect plant diseases from picture of its leaves.
This method is based on deep learning classification
which is carried out by convolutional neural networks.
Various experiments were performed using the
PlantVillage database. This database includes 54,305
images for 12 different plants for which there exists one
healthy and different number of disease classes each.
There is total of 38 classes with 26 different diseases. We
obtained 98.47% success rate for the classification of
diseases.
Anahtar kelimeler
Sürdürülebilir Kalkınma Amaçları
-
SKA 3: Sağlıklı Bireyler
-
SKA 8: İnsana Yakışır İş ve Ekonomik Büyüme
Atıf için künye
Kılıç, R., Sağlam, H. K., Oral, E. A., & Özbek, İ. Y. (2018). Detection of Plant Disease From Plant Image. ISASE2018, Erzurum.
BibTeX
@inproceedings{kilic2018-181099,
author = {Kılıç, Rabiye and Sağlam, Hilal Kübra and Oral, Emin Argun and Özbek, İbrahim Yücel},
title = {Detection of Plant Disease From Plant Image},
booktitle = {ISASE2018},
address = {Erzurum},
year = {2018},
url = {https://akademik.atauni.edu.tr/yayinlar/181099-detection-of-plant-disease-from-plant-image}
}