Benchmarking Deep Learning Models for Automatic Ultrasonic Imaging Inspection

Benchmarking Deep Learning Models for Automatic Ultrasonic Imaging Inspection

The success of deep neural networks in carrying out a wide variety of cognitive tasks also raised expectations regarding the advent of AI for the ultrasonic testing (UT) data interpretation in the Non-destructive evaluation (NDE) field. Though it is a growing area of research, we identify two main b...

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Bibliographic Details
Main Authors: Jiaxing Ye, Nobuyuki Toyama
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Anomaly detection
computer vision
deep learning
non-destructive evaluation
ultrasonic inspection
Online Access:https://ieeexplore.ieee.org/document/9366507/

Internet

https://ieeexplore.ieee.org/document/9366507/

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