Sensory Data Fusion Using Machine Learning Methods For In-Situ Defect Registration In Additive Manufacturing: A Review-Reference-Cited by-同舟云学术

Sensory Data Fusion Using Machine Learning Methods For In-Situ Defect Registration In Additive Manufacturing: A Review

Published:2022-06-01 Issue: Volume: Page:
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Container-title:2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)
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Author:

Akhavan Javid¹,Manoochehri Souran¹

Affiliation:

1. Stevens Institute of Technology,Mechanical Engineering,Hoboken,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9795657/9795699/09795815.pdf?arnumber=9795815

Reference40 articles.

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2. Effect of the ironing process on ABS parts produced by FDM

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4. Deep Multi-Modal U-Net Fusion Methodology of Infrared and Ultrasonic Images for Porosity Detection in Additive Manufacturing;zamiela;PhD thesis,2021

5. Deep fusion methodology of infrared and ultrasonic data for porosity detection in additive manufacturing;zamiela;IIE Annual Conference Proceedings,2021

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