High resolution weld semantic defect detection algorithm based on integrated double U structure DOI Creative Commons
Xiaoyan Li, Wei Yi,

Zhigang Lv

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: May 22, 2025

Language: Английский

Autonomous path generation for side-seal welding of composite plate billets based on binocular vision and lightweight network VGG16-UNet DOI

Wanyong Wang,

Haohan Sun,

Cong Chen

et al.

Robotics and Computer-Integrated Manufacturing, Journal Year: 2025, Volume and Issue: 94, P. 102969 - 102969

Published: Jan. 23, 2025

Language: Английский

Citations

1
SFW-YOLO: A lightweight multi-scale dynamic attention network for weld defect detection in steel bridge inspection DOI
Yuan Luo, Juan Ling, Jiangwei Wang

et al.

Measurement, Journal Year: 2025, Volume and Issue: unknown, P. 117608 - 117608

Published: April 1, 2025

Language: Английский

Citations

1
High-resolution weld defect detection with RSU-MLP and dynamic kernel supervision DOI
Liangliang Li, Peng Wang, Ying Li

et al.

Measurement, Journal Year: 2024, Volume and Issue: 242, P. 116208 - 116208

Published: Nov. 13, 2024

Language: Английский

Citations

3
Deep Transfer Learning + BDENet: An Innovative Approach for Detecting the Internal Defects of Weld seams Using Radiographic Imaging DOI
Mengsi Zhang, Xinyi Yu, Hua Lu

et al.

International Journal of Pressure Vessels and Piping, Journal Year: 2025, Volume and Issue: unknown, P. 105467 - 105467

Published: Feb. 1, 2025

Language: Английский

Citations

0
Small Object Geological Carbonate Detection Algorithm Based on YOLOX DOI Creative Commons
Junpeng Shi

Frontiers in Science and Engineering, Journal Year: 2025, Volume and Issue: 5(3), P. 152 - 162

Published: March 19, 2025

Detection of small object Carbonates poses a challenging task, primarily due to the minuscule nature making thcem difficult distinguish from background. Traditional methods often struggle when faced with these Carbonates, as their scale is and they exhibit minimal differences background, resulting in challenges accurate detection classification. To address this issue, study proposes an Geological Carbonate algorithm based on spatial attention combined self-attention mechanisms. This first utilizes assist model focusing regions interest containing thereby reducing background interference increasing towards Carbonates. Subsequently, mechanism employed capture long-range dependencies across entire image, aiding understanding relationship between thus facilitating better differentiation Finally, proposed evaluated public dataset TT-100k NEU, respectively. Experimental results demonstrate that compared baseline model, achieves improvement 2.4% average precision (APsmall) 3.2% overall (AP0.5) at IoU=0.5 dataset; 1.5% APsmall 1.8% AP0.5 NEU dataset.

Language: Английский

Citations

0
Transmission Line Bolt Missing Detection Based on Improved YOLOv8 Network DOI

Shounan Bao,

Chaofeng Li

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 257 - 273

Published: Jan. 1, 2025

Language: Английский

Citations

0
An efficient and scale-aware zero-shot industrial anomaly detection technique based on optimized CLIP DOI
Yahui Cheng,

Guojun Wen,

Aoshuang Luo

et al.

Measurement, Journal Year: 2025, Volume and Issue: unknown, P. 117443 - 117443

Published: April 1, 2025

Language: Английский

Citations

0
A self-configuring transformer segmentation method for welding radiographic defect detection in steel pipes DOI
Keming Guan, Yifeng Zhou, Li Wang

et al.

Nondestructive Testing And Evaluation, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 22

Published: April 13, 2025

Language: Английский

Citations

0
High resolution weld semantic defect detection algorithm based on integrated double U structure DOI Creative Commons
Xiaoyan Li, Wei Yi,

Zhigang Lv

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: May 22, 2025

Language: Английский

Citations

0