Fabric Defect Classification Using Combination of Deep Learning and Machine Learning

Fatma Günseli Yaşar Çıklaçandır; Semih Utku; Hakan Özdemir

Fabric Defect Classification Using Combination of Deep Learning and Machine Learning

Abstract

Automatic systems can be used in many areas, such as the production stage in factories, country defense, and traffic control. They provide the opportunity to reach results faster with higher success rates thanks to human-computer vision cooperation. In this study, it is aimed to develop an intelligent system that automatically detects and classifies defects in fabrics. Thanks to the developed system, the cause of the malfunction is eliminated, and the recurrence of the malfunction is prevented. Using deep learning methods in fabric defect classification studies has a disadvantage compared to other methods. Multiple layers in deep learning cause a time-consuming process. Therefore, a combination of Deep Learning and Support Vector Machines (SVM) has been used in this study. The success of the provided system has been compared with other deep learning algorithms in terms of time and accuracy.

Keywords

References

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Details

Primary Language

English

Subjects

Artificial Intelligence

Journal Section

Research Article

Authors

Fatma Günseli Yaşar Çıklaçandır ^* This is me
Türkiye

Semih Utku This is me
Türkiye

Hakan Özdemir This is me
Türkiye

Publication Date

August 30, 2021

Submission Date

July 14, 2021

Acceptance Date

August 12, 2021

Published in Issue

Year 2021 Volume: 1 Number: 1

IZ

https://izlik.org/JA23AW46FZ

Cite

RIS / Bibtex

APA

Yaşar Çıklaçandır, F. G., Utku, S., & Özdemir, H. (2021). Fabric Defect Classification Using Combination of Deep Learning and Machine Learning. Journal of Artificial Intelligence and Data Science, 1(1), 22-27. https://izlik.org/JA23AW46FZ

AMA

1.Yaşar Çıklaçandır FG, Utku S, Özdemir H. Fabric Defect Classification Using Combination of Deep Learning and Machine Learning. Journal of Artificial Intelligence and Data Science. 2021;1(1):22-27. https://izlik.org/JA23AW46FZ

Chicago

Yaşar Çıklaçandır, Fatma Günseli, Semih Utku, and Hakan Özdemir. 2021. “Fabric Defect Classification Using Combination of Deep Learning and Machine Learning”. Journal of Artificial Intelligence and Data Science 1 (1): 22-27. https://izlik.org/JA23AW46FZ.

EndNote

Yaşar Çıklaçandır FG, Utku S, Özdemir H (August 1, 2021) Fabric Defect Classification Using Combination of Deep Learning and Machine Learning. Journal of Artificial Intelligence and Data Science 1 1 22–27.

IEEE

[1]F. G. Yaşar Çıklaçandır, S. Utku, and H. Özdemir, “Fabric Defect Classification Using Combination of Deep Learning and Machine Learning”, Journal of Artificial Intelligence and Data Science, vol. 1, no. 1, pp. 22–27, Aug. 2021, [Online]. Available: https://izlik.org/JA23AW46FZ

ISNAD

Yaşar Çıklaçandır, Fatma Günseli - Utku, Semih - Özdemir, Hakan. “Fabric Defect Classification Using Combination of Deep Learning and Machine Learning”. Journal of Artificial Intelligence and Data Science 1/1 (August 1, 2021): 22-27. https://izlik.org/JA23AW46FZ.

JAMA

1.Yaşar Çıklaçandır FG, Utku S, Özdemir H. Fabric Defect Classification Using Combination of Deep Learning and Machine Learning. Journal of Artificial Intelligence and Data Science. 2021;1:22–27.

MLA

Yaşar Çıklaçandır, Fatma Günseli, et al. “Fabric Defect Classification Using Combination of Deep Learning and Machine Learning”. Journal of Artificial Intelligence and Data Science, vol. 1, no. 1, Aug. 2021, pp. 22-27, https://izlik.org/JA23AW46FZ.

Vancouver

1.Fatma Günseli Yaşar Çıklaçandır, Semih Utku, Hakan Özdemir. Fabric Defect Classification Using Combination of Deep Learning and Machine Learning. Journal of Artificial Intelligence and Data Science [Internet]. 2021 Aug. 1;1(1):22-7. Available from: https://izlik.org/JA23AW46FZ