Leveraging Segment Anything Model (SAM) for Weld Defect Detection in Industrial Ultrasonic B-Scan Images
Automated ultrasonic testing (AUT) is a critical tool for infrastructure evaluation in industries such as oil and gas, and, while skilled operators manually analyze complex AUT data, artificial intelligence (AI)-based methods show promise for automating interpretation. However, improving the reliabi...
Saved in:
Main Authors: | Amir-M. Naddaf-Sh, Vinay S. Baburao, Hassan Zargarzadeh |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/25/1/277 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Diffusion Partition Consensus: Diffusion-Aided Time-of-Flight Estimates, Anomaly Detection, and Localization for Ultrasonic Nondestructive Evaluation Data
by: Nick Torenvliet, et al.
Published: (2024-01-01) -
ClassWise-SAM-Adapter: Parameter-Efficient Fine-Tuning Adapts Segment Anything to SAR Domain for Semantic Segmentation
by: Xinyang Pu, et al.
Published: (2025-01-01) -
MONITORING SYSTEM DATA PROCESSING ALGORITHM OF WELD-BONDED COUPLING INSTALLATION OF THE MAIN PIPELINES
by: G. S. Tymchik, et al.
Published: (2015-03-01) -
Time‐domain spectra of ultrasonic wave transmitted through granite and gypsum samples containing artificial defects
by: Zhuoran Tian, et al.
Published: (2025-01-01) -
Leaf water dynamics in Coffea arabica using noncontact ultrasonic intensity measurements
by: Jose L. Castaño-Bernal, et al.
Published: (2025-03-01)