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

Öz

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.

Anahtar Kelimeler

Kaynakça

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Ayrıntılar

Birincil Dil

İngilizce

Konular

Yapay Zeka

Bölüm

Araştırma Makalesi

Yazarlar

Fatma Günseli Yaşar Çıklaçandır ^* Bu kişi benim
Türkiye

Semih Utku Bu kişi benim
Türkiye

Hakan Özdemir Bu kişi benim
Türkiye

Yayımlanma Tarihi

30 Ağustos 2021

Gönderilme Tarihi

14 Temmuz 2021

Kabul Tarihi

12 Ağustos 2021

Yayımlandığı Sayı

Yıl 2021 Cilt: 1 Sayı: 1

IZ

https://izlik.org/JA23AW46FZ

Kaynak Göster

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, ve 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 (01 Ağustos 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, ve H. Özdemir, “Fabric Defect Classification Using Combination of Deep Learning and Machine Learning”, Journal of Artificial Intelligence and Data Science, c. 1, sy 1, ss. 22–27, Ağu. 2021, [çevrimiçi]. Erişim adresi: 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 (01 Ağustos 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, vd. “Fabric Defect Classification Using Combination of Deep Learning and Machine Learning”. Journal of Artificial Intelligence and Data Science, c. 1, sy 1, Ağustos 2021, ss. 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]. 01 Ağustos 2021;1(1):22-7. Erişim adresi: https://izlik.org/JA23AW46FZ