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Source: Jitesh P. Shah, Email: jitesh2k12 '@' gmail.com, Institute: Department of Information Technology, Dharmsinh Desai University,Nadiad-387001, Gujarat, INDIA. Creator Name: Harshadkumar B. Prajapati, Email: prajapatihb.it '@' ddu.ac.in, Institute: Department of Information Technology, Dharmsinh Desai University,Nadiad-387001, Gujarat, INDIA. Creator Name: Vipul K. Dabhi, Email: vipuldabhi.it '@' ddu.ac.in, Institute: Department of Information Technology, Dharmsinh Desai University,Nadiad-387001, Gujarat, INDIA. Data Set Information: The dataset was created by manually separating infected leaves into different disease classes. We had consulted the farmers and had asked them to provide names of diseases for sample leaves. Farmers had provided names in their native languages (Gujarati) and we identiï¬ed and veriï¬ed English names of those diseases by consulting with experts of agriculture ï¬eld.
Attribute Information: Image Format: .jpg, The images were captured with a white background, in direct sunlight. The images were reduced to the desired resolution for processing. Relevant Papers: (1) Prajapati HB, Shah JP, Dabhi VK. Detection and classification of rice plant diseases. Intelligent Decision Technologies. 2017 Jan 1;11(3):357-73, doi: 10.3233/IDT-170301. (2) Shah JP, Prajapati HB, Dabhi VK. A survey on detection and classification of rice plant diseases. InCurrent Trends in Advanced Computing (ICCTAC), IEEE International Conference on 2016 Mar 10 (pp. 1-8). IEEE. Citation Request: Prajapati HB, Shah JP, Dabhi VK. Detection and classification of rice plant diseases. Intelligent Decision Technologies. 2017 Jan 1;11(3):357-73, doi: 10.3233/IDT-170301. |
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