Deep Convolutional Neural Network for Diseases Diagnosis on Plants

Please use this identifier to cite or link to this item: https://elib.vku.udn.vn/handle/123456789/2297

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DC Field	Value	Language
dc.contributor.advisor	Chu, Van Hoang	-
dc.contributor.author	Le, Thi Thu Nga	-
dc.contributor.author	Nguyen, Trung Hieu	-
dc.date.accessioned	2022-08-15T09:42:48Z	-
dc.date.available	2022-08-15T09:42:48Z	-
dc.date.issued	2022-07	-
dc.identifier.issn	978-604-84-6711-1	-
dc.identifier.uri	http://elib.vku.udn.vn/handle/123456789/2297	-
dc.description	The 11th Conference on Information Technology and its Applications; Topic: Data Science and AI; pp.02-11.	vi_VN
dc.description.abstract	Using a deep convolutional neural network helps users to diagnose diseases on plants quickly and accurately. This also helps the process of disease treatment and care become better, reduces the time, cost, and contributes to improving the quality of agricultural products. This paper proposes a new model base on Convolutional Neural Network (CNN) and transfer learning for identifying and diagnosing diseases on plants. The proposed model also has been compared with the models VGG19, ResNet50 and DenseNet12. The highest accuracy of 95% was achieved from the proposed model. The measurement of F1-Score also gives the same result.	vi_VN
dc.language.iso	en	vi_VN
dc.publisher	Da Nang Publishing House	vi_VN
dc.subject	Neural Network	vi_VN
dc.subject	Deep Learning	vi_VN
dc.subject	Transfer Learning	vi_VN
dc.subject	Plant	vi_VN
dc.subject	Disease Diagnosis	vi_VN
dc.title	Deep Convolutional Neural Network for Diseases Diagnosis on Plants	vi_VN
dc.type	Working Paper	vi_VN
Appears in Collections:	CITA 2022

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