Zobrazeno 1 - 10
of 1 275
pro vyhledávání: '"surface-defect detection"'
Publikováno v:
Robotic Intelligence and Automation, 2024, Vol. 44, Issue 6, pp. 817-829.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/RIA-03-2024-0065
Autor:
Shuangning Liu, Junfeng Li
Publikováno v:
Complex & Intelligent Systems, Vol 11, Iss 1, Pp 1-19 (2024)
Abstract In order to address challenges such as small target sizes, low contrast, significant intra-class variations, and indistinct inter-class differences in surface defect detection, this paper proposes the Enhanced Context-aware Parallel Fusion N
Externí odkaz:
https://doaj.org/article/5b10a0bce210425082aa0b50549a4f7d
Autor:
Chengyu Hu, Jianxin Guo, Hanfei Xie, Qing Zhu, Baoxi Yuan, Yujie Gao, Xiangyang Ma, Jialu Chen
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-28 (2024)
Abstract Compared to the surface defect detection of industrial products produced according to specified processes, the detection of surface defects in naturally grown red jujubes poses unique and significant challenges for researchers. The high dive
Externí odkaz:
https://doaj.org/article/be62f9ec8aa64e3ab6d99f9743611c2a
Publikováno v:
Foundations of Computing and Decision Sciences, Vol 49, Iss 3, Pp 261-285 (2024)
Surface defect detection on wafers is crucial for quality control in semiconductor manufacturing. However, the complexity of defect spatial features, including mixed defect types, large scale differences, and overlapping, results in low detection acc
Externí odkaz:
https://doaj.org/article/ffb2049080734790938cceac72d76b0c
Publikováno v:
Chinese Journal of Mechanical Engineering, Vol 37, Iss 1, Pp 1-21 (2024)
Abstract Ensuring high product quality is of paramount importance in pharmaceutical drug manufacturing, as it is subject to rigorous regulatory practices. This study presents a research focused on the development of an on-line detection method and sy
Externí odkaz:
https://doaj.org/article/43c45544f8984d2aad04530d8f404f46
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract The precise identification of surface imperfections in steel strips is crucial for ensuring steel product quality. To address the challenges posed by the substantial model size and computational complexity in current algorithms for detecting
Externí odkaz:
https://doaj.org/article/3c69bdffb5874501810cac6dcb5d2387
Publikováno v:
Gong-kuang zidonghua, Vol 50, Iss 9, Pp 108-114, 166 (2024)
In response to the challenges of acquiring and labeling defect data on conveyor belts, as well as the low accuracy of deep learning-based conveyor belt defect detection methods due to unstable factors and data fluctuations in working environments, th
Externí odkaz:
https://doaj.org/article/d31c272c0ab042efa1f94a1d4213dd0b
Publikováno v:
PeerJ Computer Science, Vol 10, p e2224 (2024)
Surface defect inspection methods have proven effective in addressing casting quality control tasks. However, traditional inspection methods often struggle to achieve high-precision detection of surface defects in castings with similar characteristic
Externí odkaz:
https://doaj.org/article/84282d974e144108b21982cc4dc24c7b
Autor:
Xiao, Hongyong a, Zhang, Wenying a, Zuo, Lei a, Wen, Long a, b, d, ⁎, Li, Qingzhe a, Li, Xinyu c
Publikováno v:
In Advanced Engineering Informatics March 2025 64
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Surface defects on steel, arising from factors like steel composition and manufacturing techniques, pose significant challenges to industrial production. Efficient and precise detection of these defects is crucial for enhancing production ef
Externí odkaz:
https://doaj.org/article/16633cc1827d4bed8cb4f2bab3fc46be