Simulation-Based Data Augmentation for the Quality Inspection of Structural Adhesive With Deep Learning-Reference-Cited by-同舟云学术

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Simulation-Based Data Augmentation for the Quality Inspection of Structural Adhesive With Deep Learning

Published:2021 Issue: Volume:9 Page:76532-76541
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Peres Ricardo Silva^ORCID,Guedes Magno^ORCID,Miranda Fabio^ORCID,Barata Jose^ORCID

Funder

FCT/MCTES

Compete 2020 Program of the European Union within the Scope of the SEE-Q Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9312710/09438624.pdf?arnumber=9438624

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3. Evaluating the effect of curing conditions on the glass transition of the structural adhesive using conditional tabular generative adversarial networks;Engineering Applications of Artificial Intelligence;2024-04

4. Synthetic Simulated Data for Construction Automation: A Review;Construction Research Congress 2024;2024-03-18

5. Enhancing titanium spacer defect detection through reinforcement learning-optimized digital twin and synthetic data generation;Journal of Electronic Imaging;2024-01-19

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