Corn Leaf Diseases Recognition Based on Convolutional Neural Network

Mutia Fadhilla; Des Suryani; Ause Labellapansa; Hendra Gunawan

doi:10.25299/itjrd.2023.13904

Authors

Mutia Fadhilla Department of Informatics Engineering, Universitas islam Riau
Des Suryani Department of Informatics Engineering, Universitas islam Riau
Ause Labellapansa Department of Informatics Engineering, Universitas islam Riau
Hendra Gunawan Department of Informatics Engineering, Universitas islam Riau

DOI:

https://doi.org/10.25299/itjrd.2023.13904

Keywords:

Corn Leaf Diseases, Computer Vision, Leaf Diseases Recognition, Convolutional Neural Network, Deep Learning

Abstract

Maize or known as corn is one of the most important agricultural commodities in Indonesia beside rice. Indonesia is located in a tropical area which has high rate of rainfall and humidity which makes it easy for fungi and bacteria that caused plant disease to thrive. It could be a threat which is a decrease of corn harvest due to plant diseases. To prevent this, a deep learning approach can be implemented to recognize plant diseases automatically based on visual pattern on leaves. In this study, we proposed a CNN-based model for corn leaf diseases recognition. Based on the results, the proposed method has great performance which accuracy score of 93%. Besides that, the proposed method achieved up to 100% precision and recall, and up to 99% F1 score.

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