Deep Learning for Ultrasonic Crack Characterization in NDE
Machine learning for nondestructive evaluation (NDE) has the potential to bring significant improvements in defect characterization accuracy due to its effectiveness in pattern recognition problems. However, the application of modern machine learning methods to NDE has been obstructed by the scarcit...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on ultrasonics, ferroelectrics, and frequency control. - 1986. - 68(2021), 5 vom: 01. Mai, Seite 1854-1865
|
|---|
| 1. Verfasser: |
Pyle, Richard J
(VerfasserIn) |
|---|
| Weitere Verfasser: |
Bevan, Rhodri L T,
Hughes, Robert R,
Rachev, Rosen K,
Ali, Amine Ait Si,
Wilcox, Paul D |
|---|
| Format: | Online-Aufsatz
|
|---|
| Sprache: | English |
|---|
| Veröffentlicht: |
2021
|
|---|
| Zugriff auf das übergeordnete Werk: | IEEE transactions on ultrasonics, ferroelectrics, and frequency control
|
|---|
| Schlagworte: | Journal Article |
|---|