Estimation of Energy and Time Usage in 3D Printing With Multimodal Neural Network-Reference-Cited by-同舟云学术

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Estimation of Energy and Time Usage in 3D Printing With Multimodal Neural Network

Published:2022-12-02 Issue: Volume: Page:
ISSN:
Container-title:2022 4th International Conference on Frontiers Technology of Information and Computer (ICFTIC)
language:
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Author:

Cheng Qisen¹,Zhang Chang²,Shen Xiang³

Affiliation:

1. University of Michigan,Department of Electrical Engineering and Computer Science,Ann Arbor,USA

2. University of Minnesota,Department of Chemical Engineering and Materials Science,Minneapolis,USA

3. Georgia Washington University,Department of Statistics,Washington, D.C.,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10073966/10075087/10075130.pdf?arnumber=10075130

Reference11 articles.

1. Using Autoencoder Voxel Patterns to Predict Part Mass, Required Support Material, and Build Time;murphy;Solid Freeform Fabrication Symposium,2018

2. 3DGates

3. Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks

4. A bidirectional Knudsen pump with superior thermal management for micro-gas chromatography applications

5. A Bidirectional Knudsen Pump with a 3D-Printed Thermal Management Platform

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