DETECTION OF DISEASE ON CORN PLANTS USING CONVOLUTIONAL NEURAL NETWORK METHODS
DOI:
https://doi.org/10.21609/jiki.v12i1.695Keywords:
Convolutional Neural Network, Corn Plants, Deep Learning.Abstract
Deep Learning is still an interesting issue and is still widely studied. In this study Deep Learning was used for the diagnosis of corn plant disease using the Convolutional Neural Network (CNN) method, with a total dataset of 3.854 images of diseases in corn plants, which consisted of three types of corn diseases namely Common Rust, Gray Leaf Spot, and Northern Leaf Blight. With an accuracy of 99%, in detecting disease in corn plants.
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Published
2019-03-01
How to Cite
Hidayat, A., Darusalam, U., & Irmawati, I. (2019). DETECTION OF DISEASE ON CORN PLANTS USING CONVOLUTIONAL NEURAL NETWORK METHODS. Jurnal Ilmu Komputer Dan Informasi, 12(1), 51–56. https://doi.org/10.21609/jiki.v12i1.695
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