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  1. University of Computer Studies, Yangon
  2. Conferences

Classification of Peanut Leaves Disease using Back Propagation Neural Network

http://hdl.handle.net/20.500.12678/0000003445
http://hdl.handle.net/20.500.12678/0000003445
762a50f2-3bb7-433c-90a0-88a430187e23
78379d43-f54e-4ec4-a201-cacad4e6126f
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psc2010paper psc2010paper (239).pdf (532 Kb)
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Article
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Publication
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
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Thesis/dissertations
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