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All Journal Proceeding of the Electrical Engineering Computer Science and Informatics
I Nyoman Suryasa
Universitas Budi Luhur
Computer Science & IT Electrical & Electronics Engineering

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Wood Texture Detection with Conjugate Gradient Neural Network Algorithm Setyawan Widyarto; I Nyoman Suryasa; Otto Fajarianto; Mohd Shafry Mohd Rahim; Khairul Annuar bin Abdullah; Gigih Priyandoko; Gilang Anggit Budaya
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (449.336 KB) | DOI: 10.11591/eecsi.v4.1042

Abstract

This project explored fundamental methods to find the factors that can be used in classifying and detecting the type of wood. Whereas, the literatures have been reviewed to determine the algorithms developed. Some experiments have been conducted to analyze the model and system. The experiments are based on artificial neural network (ANN) algorithm that used back propagation and conjugate gradient method of training function in the process of identification. The experiments carried out to be more accurate than the ANN system, the result is about 96% accuracy. It is expected the method can be used and applied for the detection of the type and classification of wood in the industrial sector, especially agriculture
Co-Authors Gilang Anggit Budaya Khairul Annuar bin Abdullah Mohd Shafry Mohd Rahim Otto Fajarianto Setyawan Widyarto