Proceeding of the Electrical Engineering Computer Science and Informatics
Vol 4: EECSI 2017

Wood Texture Detection with Conjugate Gradient Neural Network Algorithm

Setyawan Widyarto (Universitas Budi Luhur)
I Nyoman Suryasa (Universitas Budi Luhur)
Otto Fajarianto (Universitas Budi Luhur)
Mohd Shafry Mohd Rahim (Universiti Teknologi Malaysia)
Khairul Annuar bin Abdullah (Universiti Selangor)
Gigih Priyandoko (Universiti Malaysia)
Gilang Anggit Budaya (Universitas Gajah Mada)

Article Info

Publish Date
01 Nov 2017

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

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Journal Info
Proceeding of the Electrical Engineering Computer Science and Informatics
Website

Abbrev

EECSI

Publisher

Institute of Advanced Engineering and Science

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Proceeding of the Electrical Engineering Computer Science and Informatics publishes papers of the "International Conference on Electrical Engineering Computer Science and Informatics (EECSI)" Series in high technical standard. The Proceeding is aimed to bring researchers, academicians, scientists, ...