A Deep Learning Approach for Artifact Suppression in MEMS-based Airborne Ultrasonic Transceivers
Author:
Affiliation:
1. Infineon Technologies AG,Neubiberg,Germany
2. Technical University of Munich,Chair for Design Automation,Munich,Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10306337/10306342/10308240.pdf?arnumber=10308240
Reference12 articles.
1. Ultrasonic image denoising using machine learning in point contact excitation and detection method
2. Performance enhancement of convolutional neural network for ultrasonic flaw classification by adopting autoencoder
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4. Autoencoders;bank,2020
5. Time-of-flight measurement techniques for airborne ultrasonic ranging
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