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State of Art Survey on Plant Leaf Disease Detection
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Optimal Compression of Remote Sensing Images Using Deep Learning during Transmission of Data
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OverFeat Network Algorithm for Fabric Defect Detection in Textile Industry
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VIRTUAL RESTORATION OF DAMAGED ARCHEOLOGICAL ARTIFACTS OBTAINED FROM EXPEDITIONS USING 3D VISUALIZATION
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Home / Archives / Volume-3 / Issue-4 / Article-3

Volume - 3 | Issue - 4 | december 2021

OverFeat Network Algorithm for Fabric Defect Detection in Textile Industry
Pages: 311-321
Published
18 December, 2021
Abstract

Automation of systems emerged since the beginning of 20th century. In the early days, the automation systems were developed with a fixed algorithm to perform some specific task in a repeated manner. Such fixed automation systems are revolutionized in recent days with an artificial intelligence program to take decisions on their own. The motive of the proposed work is to train a textile industry system to automatically detect the defects presence in the generated fabrics. The work utilizes an OverFeat network algorithm for such training process and compares its performances with its earlier version called AlexNet and VGG. The experimental work is conducted with a fabric defect dataset consisting of three class images categorised as horizontal, vertical and hole defects.

Keywords

OverFeat network textile automation fabric defect detection computer vision on fabrics AlexNet

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