Zobrazeno 1 - 10
of 813
pro vyhledávání: '"fabric defect"'
Publikováno v:
Data in Brief, Vol 57, Iss , Pp 111165- (2024)
The FabricSpotDefect dataset is, to the best of our knowledge, the first dataset specifically designed to accurately challenge computer vision in detecting fabric spots. There are a total of 1014 raw images and manually annotated 3288 different categ
Externí odkaz:
https://doaj.org/article/7b4874c2d97d4d8eb3ccc42c30bdfda7
Publikováno v:
Journal of Natural Fibers, Vol 21, Iss 1 (2024)
The scarcity of high-quality annotated data poses a significant challenge to the application of deep learning in fabric defect tasks, limiting the generalization and segmentation performance of existing models and impeding their capability to address
Externí odkaz:
https://doaj.org/article/1c8c2aff5c434cde92ce3f9242fac73a
Publikováno v:
Journal of Natural Fibers, Vol 21, Iss 1 (2024)
The current advanced neural network models are expanding in size and complexity to achieve improved detection accuracy. This study designs a lightweight fabric defect detection algorithm based on YOLOv7-tiny, called YOLOv7-tiny-MGCK. Its objectives a
Externí odkaz:
https://doaj.org/article/a4cd021ce1274015bb3affcbe29ef138
Autor:
Xueshen Li, Yong Zhu
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 3, Pp 3371-3387 (2024)
Abstract As a practical and challenging task, deep learning-based methods have achieved effective results for fabric defect detection, however, most of them mainly target detection accuracy at the expense of detection speed. Therefore, we propose a f
Externí odkaz:
https://doaj.org/article/5f24b85eb42a4c9b94e9fde4c586bbb3
Publikováno v:
IEEE Access, Vol 12, Pp 63777-63808 (2024)
Fabric defect detection is a crucial step of quality control in textile enterprises. The use of computer vision inspection technology in the textile industry is key to achieving intelligent manufacturing. This study sought to determine the progress m
Externí odkaz:
https://doaj.org/article/c833b02aba4444b4be12e806bdbc1a18
Publikováno v:
International Journal of Clothing Science and Technology, 2023, Vol. 35, Issue 6, pp. 865-888.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJCST-03-2022-0032
Publikováno v:
Engineering Science and Technology, an International Journal, Vol 53, Iss , Pp 101681- (2024)
Fabric defects can significantly impact the quality of a textile product. By analyzing the types and frequencies of defects, manufacturers can identify process inefficiencies, equipment malfunctions, or operator errors. Although deep learning network
Externí odkaz:
https://doaj.org/article/5948b7d6d7ee4fe49bd81bad477dad53
Publikováno v:
Information, Vol 15, Iss 8, p 476 (2024)
Defect detection is very important for guaranteeing the quality and pricing of fabric. A considerable amount of fabric is discarded as waste because of defects, leading to substantial annual losses. While manual inspection has traditionally been the
Externí odkaz:
https://doaj.org/article/6c9615ca85774f89a971fcf931ac6f8c
Publikováno v:
Applied Sciences, Vol 14, Iss 12, p 5298 (2024)
Detecting anomalies in texture has become a significant concern across various industrial processes. One prevalent application of this is in inspecting patterned textures, especially in the domain of fabric defect detection, which is a commonly encou
Externí odkaz:
https://doaj.org/article/2017a90955fd42b89c0e88015f94a69f
Publikováno v:
Journal of Natural Fibers, Vol 20, Iss 2 (2023)
ABSTRACTFabric is produced by the weaving process through the interlacement of warp and weft yarn or knitting process through the loop formation of yarn. During these processes, there is a possibility of fabric defect formation which hinders the acce
Externí odkaz:
https://doaj.org/article/db2e8198cf7644f7bed186d6c396eed8