Comparative study on the effect of activation functions in neural network for rubber tree diseases detection

The rubber tree (Hevea brasiliensis) is grown extensively in South-East Asia, especially in Malaysia, for the production of natural rubber and, increasingly, timber. However, rubber tree generally attacked by pests or diseases such as root disease, white root, red root, brown root, leaf disease and...

Full description

Saved in:

Bibliographic Details
Main Author:	Mohd. Rasidi, Haryani
Format:	Thesis
Language:	English
Published:	2011
Subjects:	Q Science (General)
Online Access:	http://eprints.utm.my/id/eprint/32825/5/HaryaniMohdRasidiMFSKSM2011.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-utm-ep.32825
record_format	uketd_dc
spelling	my-utm-ep.328252018-05-27T07:55:14Z Comparative study on the effect of activation functions in neural network for rubber tree diseases detection 2011-05 Mohd. Rasidi, Haryani Q Science (General) The rubber tree (Hevea brasiliensis) is grown extensively in South-East Asia, especially in Malaysia, for the production of natural rubber and, increasingly, timber. However, rubber tree generally attacked by pests or diseases such as root disease, white root, red root, brown root, leaf disease and the others. In this study, four types of diseases will be seen namely Fusicoccum, Corynespora, Collelotrichum and Oidium. Generally known that neural networks may be used for nonlinear analysis of complex data. As such, the purpose of this study is to evaluate the usefulness of Artificial Neural Networks (ANNs) applied to rubber tree for diseases detection. The ANNs used in the present study were based on a feed forward layered model with input, hidden, and output layers, on which a backpropagation learning model was implemented. The focus of study also to investigate the effect of activation functions on accuracy, efficiency and performance of disease detection. Four activation functions will be compare which are Hyperbolic Tangent Sigmoid, Linear, Radial Basis and Triangular. This study also will be focus on how to convert an image data to the conventional input data. The preprocessing process of the sample image such as image enhancement, image filtering has been performed before the process feature extraction will be applied. The techniques that will be used for feature extraction of image using the gabor filter method. The output of this filter will be used for the classification purpose in order to determine the characteristics of rubber tree diseases image. 10-fold cross validation techniques will be applied in order to measure the percentage of accurately of this classifier. 2011-05 Thesis http://eprints.utm.my/id/eprint/32825/ http://eprints.utm.my/id/eprint/32825/5/HaryaniMohdRasidiMFSKSM2011.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computer Science and Information System Faculty of Computer Science and Information System
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	Q Science (General)
spellingShingle	Q Science (General) Mohd. Rasidi, Haryani Comparative study on the effect of activation functions in neural network for rubber tree diseases detection
description	The rubber tree (Hevea brasiliensis) is grown extensively in South-East Asia, especially in Malaysia, for the production of natural rubber and, increasingly, timber. However, rubber tree generally attacked by pests or diseases such as root disease, white root, red root, brown root, leaf disease and the others. In this study, four types of diseases will be seen namely Fusicoccum, Corynespora, Collelotrichum and Oidium. Generally known that neural networks may be used for nonlinear analysis of complex data. As such, the purpose of this study is to evaluate the usefulness of Artificial Neural Networks (ANNs) applied to rubber tree for diseases detection. The ANNs used in the present study were based on a feed forward layered model with input, hidden, and output layers, on which a backpropagation learning model was implemented. The focus of study also to investigate the effect of activation functions on accuracy, efficiency and performance of disease detection. Four activation functions will be compare which are Hyperbolic Tangent Sigmoid, Linear, Radial Basis and Triangular. This study also will be focus on how to convert an image data to the conventional input data. The preprocessing process of the sample image such as image enhancement, image filtering has been performed before the process feature extraction will be applied. The techniques that will be used for feature extraction of image using the gabor filter method. The output of this filter will be used for the classification purpose in order to determine the characteristics of rubber tree diseases image. 10-fold cross validation techniques will be applied in order to measure the percentage of accurately of this classifier.
format	Thesis
qualification_level	Master's degree
author	Mohd. Rasidi, Haryani
author_facet	Mohd. Rasidi, Haryani
author_sort	Mohd. Rasidi, Haryani
title	Comparative study on the effect of activation functions in neural network for rubber tree diseases detection
title_short	Comparative study on the effect of activation functions in neural network for rubber tree diseases detection
title_full	Comparative study on the effect of activation functions in neural network for rubber tree diseases detection
title_fullStr	Comparative study on the effect of activation functions in neural network for rubber tree diseases detection
title_full_unstemmed	Comparative study on the effect of activation functions in neural network for rubber tree diseases detection
title_sort	comparative study on the effect of activation functions in neural network for rubber tree diseases detection
granting_institution	Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department	Faculty of Computer Science and Information System
publishDate	2011
url	http://eprints.utm.my/id/eprint/32825/5/HaryaniMohdRasidiMFSKSM2011.pdf
_version_	1747816069619253248

Comparative study on the effect of activation functions in neural network for rubber tree diseases detection

Similar Items