Application of neural network technologies in the tasks of quality control of textile products

Abstract

Application of neural network technologies in the tasks of quality control of textile products

Kaznacheeva A.A., Vlasenko O.M., Zakharkina S.V., Stupak M.M.

Incoming article date: 05.12.2023

The problem of developing an intelligent automated system for detecting defects in textile materials is considered. An analysis of machine learning and deep learning algorithms was carried out in relation to solving the problem of product quality control. The implementation of an artificial neural network implemented in a Raspberry Pi microcomputer and receiving a set of input data in the form of a large stream of images from a high-speed digital camera is considered. The stages of creating a model in Python using the TensorFlow and Keras libraries are described. The development process includes the preparation of initial data intended for training and testing the system, as well as testing the operation of the resulting neural network, which consists in recognizing images of defects on fabric according to classification criteria.

Keywords: machine learning, neural network, defect images, textile material, training, testing, accuracy