Zobrazeno 1 - 10
of 156
pro vyhledávání: '"CARAFE"'
Autor:
Yuanyuan Wang, Tongtong Yin, Xiuchuan Chen, Abdullahi Suleiman Hauwa, Boyang Deng, Yemeng Zhu, Shangbing Gao, Haiyan Zang, Hu Zhao
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-21 (2024)
Abstract Scratches and cracks in steel severely affect its service life and performance. However, owing to the irregular shapes and sizes of steel surface defects, defects within the same class may be different, whereas defects between classes may be
Externí odkaz:
https://doaj.org/article/0bceb197b50f4c71865ec3329f8d52c2
Publikováno v:
AIMS Mathematics, Vol 9, Iss 5, Pp 10775-10801 (2024)
Fire is a common but serious disaster, which poses a great threat to human life and property. Therefore, fire-smoke detection technology is of great significance in various fields. In order to improve the detection ability of tiny-fire, so as to real
Externí odkaz:
https://doaj.org/article/4658cbd927904625ba5f12fd3474ee19
Publikováno v:
IEEE Access, Vol 12, Pp 137667-137682 (2024)
The detection of surface defects on printed circuit board (PCB) plays a vital role. However, current defect detection methods face significant challenges, such as frequently misidentifying non-defective areas as defects, low defect recognition capabi
Externí odkaz:
https://doaj.org/article/07c3afb3fb574e1287010f6464c4dfe0
Publikováno v:
IEEE Access, Vol 12, Pp 109886-109899 (2024)
Crop diseases and pests cause significant economic losses to agriculture every year, making accurate identification crucial. Traditional pest and disease detection relies on farm experts, which is often time-consuming. Computer vision technology and
Externí odkaz:
https://doaj.org/article/b17e5559aa8949d8be76560ca703b303
Publikováno v:
IEEE Access, Vol 12, Pp 95106-95117 (2024)
Considering steel as one of the most widely utilized materials, the detection of defects on its surface has always been a paramount area of research. Traditional target detection algorithms often face challenges such as low detection accuracy, missed
Externí odkaz:
https://doaj.org/article/506c8fadd298422f852307990ce6abfb
Publikováno v:
IEEE Access, Vol 12, Pp 69633-69641 (2024)
Aiming at the problem of low visibility of underwater environment, which leads to the leakage of small target detection and low accuracy, this paper proposes an improved algorithm USSTD-YOLOv8n (Underwater small-size target detection YOLOv8n) based o
Externí odkaz:
https://doaj.org/article/36ef854b53004bd3a54d0332a4a2f3d8
Autor:
Kaixin Wang, Xihong Hu, Huiwen Zheng, Maoyang Lan, Changjiang Liu, Yihui Liu, Lei Zhong, Hai Li, Suiyan Tan
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
IntroductionThe precise detection of weeds in the field is the premise of implementing weed management. However, the similar color, morphology, and occlusion between wheat and weeds pose a challenge to the detection of weeds. In this study, a CSCW-YO
Externí odkaz:
https://doaj.org/article/4221cc134932459c935cfff9e0596b31
Autor:
Yiwen Jiang
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 11, Pp 19858-19870 (2023)
To address the challenge of achieving a balance between efficiency and performance in steel surface defect detection, this paper presents a novel algorithm that enhances the YOLOv5 defect detection model. The enhancement process begins by employing t
Externí odkaz:
https://doaj.org/article/cd511852742a4faeb9d90474121eff20
Publikováno v:
Applied Sciences, Vol 14, Iss 19, p 8770 (2024)
Aiming at the problem that insulator image backgrounds are complex and fault types are diverse, which makes it difficult for existing deep learning algorithms to achieve accurate insulator fault diagnosis, an insulator fault diagnosis method based on
Externí odkaz:
https://doaj.org/article/eeb6557e18574dceb158044532336e0d
Publikováno v:
Energies, Vol 17, Iss 19, p 4767 (2024)
Detecting defects in aerial images of grading rings collected by drones poses challenges due to the structural similarity between normal and defective samples. The small visual differences make it hard to distinguish defects and extract key features.
Externí odkaz:
https://doaj.org/article/8124598ddcdf4528be078a48bd08f495