International Journal of Scientific Development and Research - IJSDR
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Issue: July 2021

Volume 6 | Issue 7

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Paper Title: Wood Defects Classification Using Generalized Feed-Forward Neural Network
Authors Name: Ms.Bhagyashri Umesh Vaidya , Dr.V.L Agrawal
Unique Id: IJSDR2106019
Published In: Volume 6 Issue 6, June-2021
Abstract: In this paper a new classification algorithm is proposed for the Wood Defects. In order to develop algorithm 158 different wood defect images With a view to extract features from the images after using matlab, an algorithm proposes (FFT) Fast Fourier Transform coefficients. The Efficient classifiers based on Generalized Feed-Forward Neural Networks (GFF NN). A separate Cross-Validation dataset is employed for correct evaluation of the proposed classification algorithm with reference to important performance measures, like MSE and classification accuracy. The Average Classification Accuracy of GFF Neural Network comprising of hidden layers1 with 50 PE’s organized in a typical system is found to be superior (97.5 %) for Training. Finally, optimal algorithm has been developed on the idea of the simplest classifier performance. The algorithm will provide an effective alternative to traditional method of wood defects analysis for deciding the best quality wood.
Keywords: Matlab, Nero Solution Software, Microsoft excel, GFF Neural network, FFT Transform Techniques
Cite Article: "Wood Defects Classification Using Generalized Feed-Forward Neural Network ", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.6, Issue 6, page no.127 - 132, June-2021, Available :http://www.ijsdr.org/papers/IJSDR2106019.pdf
Downloads: 00025284
Publication Details: Published Paper ID: IJSDR2106019
Registration ID:193402
Published In: Volume 6 Issue 6, June-2021
DOI (Digital Object Identifier):
Page No: 127 - 132
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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