Zobrazeno 1 - 10
of 749
pro vyhledávání: '"defect recognition"'
Autor:
Saúl Cano-Ortiz, Eugenio Sainz-Ortiz, Lara Lloret Iglesias, Pablo Martínez Ruiz del Árbol, Daniel Castro-Fresno
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Deep learning-based computer vision systems have become powerful tools for automated and cost-effective pavement distress detection, essential for efficient road maintenance. Current methods focus primarily on developing supervised learning
Externí odkaz:
https://doaj.org/article/d85de472a532401ea12c8c6fcf97f3eb
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
In today’s era of rapid technological advancement, the emergence of drone technology and intelligent power systems has brought tremendous convenience to society. However, the challenges associated with drone image recognition and intelligent grid d
Externí odkaz:
https://doaj.org/article/dd99c84d807e43d797ddae74041dfdcd
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
Cable insulation defect detection ensures electrical safety, prevents accidents, extends equipment life and guarantees stable system operation. For the traditional cable insulation defect detection and identification of difficult problems, this paper
Externí odkaz:
https://doaj.org/article/02c8ceeab46d41cb9e9c6e4d99f3da58
Autor:
Zhong, Hao a, Xiao, Ling b, Wang, Haifeng a, Zhang, Xin c, Wan, Chenhui a, Hu, Youmin a, ⁎, Wu, Bo a
Publikováno v:
In Knowledge-Based Systems 25 November 2024 304
Publikováno v:
In Expert Systems With Applications 5 April 2025 268
Publikováno v:
Proceedings on Engineering Sciences, Vol 6, Pp 281-290 (2024)
The rising advancements in Industry 4.0 technologies have made more usual to acquire significant volumes of machine operating data in real time. In response to inconsistent data distribution and label scarcity in target domains, this work suggests a
Externí odkaz:
https://doaj.org/article/871a080b9c0d458abc7a41d8afe56a29
Autor:
V.V. Kiyashchenko
Publikováno v:
Модели, системы, сети в экономике, технике, природе и обществе, Iss 1 (2024)
Background. This study addresses the issue of automated defect recognition in two-component composite coatings. The research aims to develop an efficient informationmeasuring system that utilizes modern technologies for detecting and characterizing
Externí odkaz:
https://doaj.org/article/bdc048d3955e47da87485f0d613a4f09
Publikováno v:
IEEE Access, Vol 12, Pp 158436-158445 (2024)
The paper proposes PCB-DETR, a novel detection network for PCB surface defect identification, which enhances the performance of small defect detection through improvements to the Deformable-DETR model. Traditional supervised learning methods demonstr
Externí odkaz:
https://doaj.org/article/e88d8c7a8d7047acb0a4ff402aa03faf
Publikováno v:
Engineering Computations, 2023, Vol. 40, Issue 6, pp. 1305-1329.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/EC-12-2022-0720
Publikováno v:
Biomimetics, Vol 9, Iss 10, p 607 (2024)
Strip steel surface defect recognition research has important research significance in industrial production. Aiming at the problems of defect feature extraction, slow detection speed, and insufficient datasets, YOLOv5 is improved on the basis of YOL
Externí odkaz:
https://doaj.org/article/ce95e86ad0304a42bcd2026f16fed2ec