title: ÐÐ±Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð½ÐµÐ¾Ð±Ñ Ð¾Ð´Ð¸Ð¼Ð¾ÑÑÐ¸ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ Ð¸ Ð²Ð½ÐµÐ´ÑÐµÐ½Ð¸Ñ Ð¼Ð¾Ð´ÑÐ»Ñ ÑÐ¸ÑÑÐµÐ¼Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð´ÐµÑÐµÐºÑÐ¾Ð² ÑÐºÐ°Ð½Ð¸ Ð½Ð° Ð¿ÑÐµÐ´Ð¿ÑÐ¸ÑÑÐ¸ÑÑ Ð»ÐµÐ³ÐºÐ¾Ð¹ Ð¿ÑÐ¾Ð¼ÑÑÐ»ÐµÐ½Ð½Ð¾ÑÑÐ¸ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ Ð¿Ð¾Ð´Ñ Ð¾Ð´Ð°
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Substantiation of the necessity of creation and implementation of the module of the fabric defects detection system at the light industry enterprises using neural network approach
Creators: name: ÐÑÑÐ¸Ð½, ÐÐ¼Ð¸ÑÑÐ¸Ð¹
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: Ð´ÐµÑÐµÐºÑÑ ÑÐµÐºÑÑÐ¸Ð»ÑÐ½ÑÑ Ð¼Ð°ÑÐµÑÐ¸Ð°Ð»Ð¾Ð²
Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ Ð´ÐµÑÐµÐºÑÐ¾Ð²
ÐºÐ¾Ð½ÑÑÐ¾Ð»Ñ ÐºÐ°ÑÐµÑÑÐ²Ð°
ÑÐ²ÐµÑÑÐ¾ÑÐ½ÑÐµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½Ð¾Ðµ Ð·ÑÐµÐ½Ð¸Ðµ
Ð»ÐµÐ³ÐºÐ°Ñ Ð¿ÑÐ¾Ð¼ÑÑÐ»ÐµÐ½Ð½Ð¾ÑÑÑ
Ð±ÐµÑÐµÐ¶Ð»Ð¸Ð²Ð¾Ðµ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´ÑÑÐ²Ð¾
textile fabric defects
detection of defects
quality control
convolutional neural networks
computer vision
light industry
lean production

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description: The given work is devoted to substantiation of the necessity of creation and implementation of the module of the system of textile fabric defects detection at the light industry enterprises using neural network approach. The research set the following goals: â to analyze the general state of quality control of textile fabrics; â to analyze defect detection technologies, including the use of computer vision and neural network models; â to provide software and hardware characteristics of the developed module of the defect detection system; â to analyze the results and evaluate the effectiveness of the creation and implementation of the defect detection module at the enterprise. The relevance of the work is due to the process of digitalization of light industry enterprises, which explores the possibilities of automating individual stages of the production chain, one of which is the process of defect detection, currently performed manually with unsatisfactory accuracy and has the potential for automation using modern information technology. The sources of information were the data of domestic and foreign research literature, official Internet resources and project documentation. The study resulted into analysis of the area of quality control of textile fabrics, as well as approbation of the developed module of the defect detection system using neural network approach at the enterprise, the use of which allowed increasing the accuracy of defect detection by 3.33 times, which improved the performance of key production metrics of the enterprise.