Deep Learning Modelling for Composite Properties of PCB Conductive Layers-Reference-Cited by-同舟云学术

Deep Learning Modelling for Composite Properties of PCB Conductive Layers

Published:2022-04-25 Issue: Volume: Page:
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Container-title:2022 23rd International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE)
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Author:

Stoyanov Stoyan¹,Bailey Chris¹

Affiliation:

1. University of Greenwich,Computational Mechanics and Reliability Group, School of Computing and Mathematical Sciences,London,United Kingdom,SE10 9LS

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9758836/9758837/09758885.pdf?arnumber=9758885

Reference14 articles.

1. Neural Network for Mechanical Property Estimation of Multi-layered Laminate Composite;barbosa;Materials Today Proceedings,0

2. Predicting Materials Properties with Little Data Using Shotgun Transfer Learning

3. Predictions of the mechanical properties of unidirectional fibre composites by supervised machine learning

4. Prediction and optimization of mechanical properties of composites using convolutional neural networks

5. Conceptual Understanding of Convolutional Neural Network- A Deep Learning Approach

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