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Classification of Peanut Leaves Disease using Back Propagation Neural Network
http://hdl.handle.net/20.500.12678/0000003445
http://hdl.handle.net/20.500.12678/0000003445762a50f2-3bb7-433c-90a0-88a430187e23
78379d43-f54e-4ec4-a201-cacad4e6126f
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psc2010paper (239).pdf (532 Kb)
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Article | ||||||
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Title | ||||||
Title | Classification of Peanut Leaves Disease using Back Propagation Neural Network | |||||
Language | en | |||||
Publication date | 2010-12-16 | |||||
Authors | ||||||
Maw, Naw Aye Aye | ||||||
Htay, Sandar | ||||||
Description | ||||||
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. | ||||||
Keywords | ||||||
Peanut Leaves Disease, Back- Propagation Algorithm, Artificial Neural Network | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/1194 | |||||
Journal articles | ||||||
Fifth Local Conference on Parallel and Soft Computing | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |