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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Abdessamad Balouki
University of Sultan Moulay Slimane
Computer Science & IT Engineering

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Fabric defect classification using transfer learning and deep learning Aafaf Beljadid; Adil Tannouche; Abdessamad Balouki
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i3.pp1378-1385

Abstract

The internal inspection of fabrics is one of the most important phases of production in order to achieve high quality standard in the textile industry. Therefore, developing efficient automatic internal control mechanism has been an extremely major area of research. In this paper, the famous architecture GoogLeNet was fine-tuned into two configurations for texture defect classification that was trained on a textile texture database (TILDA). The experimental result, for both configurations, achieved a significant overall accuracy score of 97% for motif and a non-motif-based images and 89% for mixed images. In the results obtained, it was observed that the second model, which updates the last six layers, was more successful than the first one; which updates the last two layers.
Co-Authors aafaf beljadid Adil Tannouche