Investigation of multi-input convolutional neural networks for the prediction of particleboard mechanical properties

Investigation of multi-input convolutional neural networks for the prediction of particleboard mechanical properties

Abstract This study explored the potential of building an image-based quality control system for particleboard manufacturing. Single-layer particleboards were manufactured under 27 operating conditions and their modulus of elasticity (MOE) and the modulus of rupture (MOR) were determined. Subsequent...

Full description

Saved in:
Bibliographic Details
Main Authors: Shuoye Chen, Shunsuke Sakai, Miyuki Matsuo-Ueda, Kenji Umemura
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Subjects:
Convolutional neural network
Property prediction
Deep learning
Mechanical properties
Particleboard
Online Access:https://doi.org/10.1038/s41598-025-88301-z
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items