Attention U-Net-based semantic segmentation for welding line detection
Abstract In industrial processes, quality assurance through methods such as visual inspection is essential for ensuring process stability. Traditional manual visual inspection is a time-consuming and costly endeavor. If the opportunity arises, replacing manual visual inspection with AI could lead to...
Saved in:
| Main Authors: | Hunor István Lukács, Bence Zsolt Beregi, Balázs Porteleki, Tamás Fischl, János Botzheim |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-00257-2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A survey of semantic applications in communications
by: Yingzi XU, et al.
Published: (2022-05-01) -
Measuring Semantic Stability: Statistical Estimation of Semantic Projections via Word Embeddings
by: Roger Arnau, et al.
Published: (2025-05-01) -
Weld Pool Boundary Detection Based on the U-Net Algorithm and Weld Seam Tracking in Plasma Arc Welding
by: Jidong Lu, et al.
Published: (2025-02-01) -
Intelligent Sensor Software for Robust and Energy-Sustainable Decision-Making in Welding of Steel Reinforcement for Concrete
by: Javier Ferreiro-Cabello, et al.
Published: (2024-12-01) -
High resolution weld semantic defect detection algorithm based on integrated double U structure
by: Xiaoyan Li, et al.
Published: (2025-05-01)