Fabric Defect Classification Using Combination of Deep Learning and Machine Learning

Fatma Günseli YAŞAR ÇIKLAÇANDIR

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 o ...Daha fazlası

Makale 2021 Journal of Artificial Intelligence and Data Science1 ( 1 ) , pp. 2 - 27 29 Görüntülenme

Erişime Açık

Estimation of Scattering Parameters of U-Slotted Rectangular RFID Patch Antenna with Machine Learning Models

İsmail AKDAĞ

Abstract In this study, machine learning-based models have been used to estimate the return loss parameters of the operational resonant frequency of the U-slotted UHF RFID antenna. The data set utilized, consisting of 544 instances, has been collected from the simulation software as a consequence of the parametric evaluation of the antenna design parameters. Distinct machine learning methods have been used on two different types of output data, complex and linear scattering parameters, and the models' prediction performance has been evaluated. In the single-output regression models, a mean-squ ...Daha fazlası

Makale 2021 Journal of Artificial Intelligence and Data Science1 ( 1 ) , pp. 6 - 70 19 Görüntülenme