|Table of Contents|

Fabric pattern classification based on depth convolution neural network(PDF)

《纺织高校基础科学学报》[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2017年02期
Page:
261-265
Research Field:
Publishing date:

Info

Title:
Fabric pattern classification based on depth convolution neural network
Author(s):
 ZHANG HongweiZHANG LingjieLI Pengfei
 School of Electronics and Information, Xi’an Polytechnic University, Xi’an 710048, China
Keywords:
 depth convolution neural network fabric pattern image analysis
PACS:
TP 391
DOI:
10.13338/j.issn.1006-8341.2017.02.017
Abstract:
 To solve low efficiency problems of fabric pattern artificial visual classification, a method to classify fabric strip,lattice and wave point patterns based on depth convolution neural network(CNN)is presented. First,image samples and tag data are constructed, which include fabric strip,lattice and wave point patterns. Then,fabric pattern classification models are developed based on GoogLeNet and AlexNet CNN, respectively. Finally,optimal training epoch periods are selected by the model evaluation method. Experimental results indicate that it is feasible and effective to classify fabric patterns by deep convolution neural networks.

References:

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Last Update: 2017-07-22