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Classification of Peanut Leaves Disease using Back Propagation Neural Network

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dc.contributor.author Maw, Naw Aye Aye
dc.contributor.author Htay, Sandar
dc.date.accessioned 2019-07-23T02:44:07Z
dc.date.available 2019-07-23T02:44:07Z
dc.date.issued 2010-12-16
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1194
dc.description.abstract A number of classification systems have been developed depending on the intended purpose of the system. This system tries to classify peanut leaves diseases.. The images of the peanut leaf are acquired by means of an digital imaging device, such as a scanner. The acquired color image is prepared with Image processing steps in order to get the digital image to be suitable with Neural Network. Back-Propagation Algorithm is used to train the Network in order to classify the peanut leaves diseases. In this system, there are many different types of peanut leaves diseases namely Early and Late Leaf spot, Rust, Web blotch, Leaf scorch, Alternaria Leaf spot, Phyllosticta Leaf spot, Peanut Mottle virus, Tomato Spotted wilt virus, Iron Chlorosis,and Ultraviolet radiation. en_US
dc.language.iso en en_US
dc.publisher Fifth Local Conference on Parallel and Soft Computing en_US
dc.subject Peanut Leaves Disease en_US
dc.subject Back- Propagation Algorithm en_US
dc.subject Artificial Neural Network en_US
dc.title Classification of Peanut Leaves Disease using Back Propagation Neural Network en_US
dc.type Article en_US

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